{smcl}
{com}{sf}{ul off}{txt}{.-}
      name:  {res}<unnamed>
       {txt}log:  {res}/Users/mkrain/Desktop/R&P-log.smcl
  {txt}log type:  {res}smcl
 {txt}opened on:  {res} 9 Sep 2016, 15:00:54

{com}. sum

. use "/Users/mkrain/Desktop/McEntireLeibyKrain_Interactions.dta"

. 
. sum

{txt}    Variable {c |}       Obs        Mean    Std. Dev.       Min        Max
{hline 13}{c +}{hline 56}
{space 2}responseid {c |}{res}         0
{txt}{space 3}ipaddress {c |}{res}         0
{txt}{space 7}start {c |}{res}         0
{txt}{space 9}end {c |}{res}         0
{txt}{space 6}finish {c |}{res}      1834    .9345692    .2473518          0          1
{txt}{hline 13}{c +}{hline 56}
{space 4}softopen {c |}{res}      1834    .0163577    .1268814          0          1
{txt}{space 10}c1 {c |}{res}      1834    .0856052    .2798565          0          1
{txt}{space 10}c2 {c |}{res}      1834    .0834242    .2765978          0          1
{txt}{space 10}c3 {c |}{res}      1834    .0861505    .2806627          0          1
{txt}{space 10}c4 {c |}{res}      1834     .082879    .2757744          0          1
{txt}{hline 13}{c +}{hline 56}
{space 10}c5 {c |}{res}      1834    .0839695    .2774177          0          1
{txt}{space 10}c6 {c |}{res}      1834    .0845147    .2782341          0          1
{txt}{space 10}c7 {c |}{res}      1834    .0845147    .2782341          0          1
{txt}{space 10}c8 {c |}{res}      1834    .0834242    .2765978          0          1
{txt}{space 10}c9 {c |}{res}      1834     .082879    .2757744          0          1
{txt}{hline 13}{c +}{hline 56}
{space 9}c10 {c |}{res}      1834    .0801527    .2716035          0          1
{txt}{space 9}c11 {c |}{res}      1834    .0806979    .2724449          0          1
{txt}{space 9}c12 {c |}{res}      1834    .0817884    .2741169          0          1
{txt}{space 6}knowq1 {c |}{res}      1831    2.830147    1.061542          1          5
{txt}{space 2}ineffectq2 {c |}{res}      1828    2.415755    1.317647          1          5
{txt}{hline 13}{c +}{hline 56}
knowconseq~3 {c |}{res}      1832    2.543122    1.011294          1          5
{txt}{space 3}conseqsq4 {c |}{res}      1827    1.969349    .8844165          1          5
{txt}knoweffectq5 {c |}{res}      1831    2.825232    1.063059          1          5
{txt}{space 4}appropq6 {c |}{res}      1827    4.136289    .9997437          1          5
{txt}{space 3}emotionq7 {c |}{res}      1830    2.039344     .826425          1          4
{txt}{hline 13}{c +}{hline 56}
{space 6}feelq8 {c |}{res}      1830     4.08306    .8441659          1          5
{txt}feelconseq~9 {c |}{res}      1826    2.223439    .9619719          1          5
{txt}feeleffec~10 {c |}{res}      1825    2.401644    1.032529          1          5
{txt}participa~11 {c |}{res}      1828     2.97046    1.137605          1          5
{txt}{space 2}supportq12 {c |}{res}      1832    2.467249      1.1577          1          5
{txt}{hline 13}{c +}{hline 56}
{space 6}ageq13 {c |}{res}      1829    31.74576     10.8698         18         76
{txt}{space 3}genderq14 {c |}{res}      1833    1.388434    .5029578          1          4
{txt}genderte~14a {c |}{res}         0
{txt}{space 5}educq15 {c |}{res}      1833    4.018549    1.306552          1          7
{txt}{space 5}newsq16 {c |}{res}      1832    3.787118    1.147499          1          5
{txt}{hline 13}{c +}{hline 56}
religiousq17 {c |}{res}      1829    1.364133     .754087          1          4
{txt}influenceq18 {c |}{res}      1830    2.894536    .7344694          1          4
{txt}charityef~19 {c |}{res}      1829    2.313833    .8477864          1          5
{txt}charitygi~20 {c |}{res}         0
{txt}agpetitio~21 {c |}{res}      1832    .3400655    .4738602          0          1
{txt}{hline 13}{c +}{hline 56}
unpetitio~22 {c |}{res}      1828     .345186     .475559          0          1
{txt}{space 1}donationq23 {c |}{res}      1829    .0956807    .2942333          0          1
{txt}{space 2}contactq24 {c |}{res}      1830    .2557377    .4363943          0          1
{txt}{space 5}captcha {c |}{res}      1834    3.017448    .3146207         -3          7
{txt}captchadic~s {c |}{res}      1834    .9934569    .0806462          0          1
{txt}{hline 13}{c +}{hline 56}
{space 5}consent {c |}{res}      1834           1           0          1          1
{txt}{space 3}mturkcode {c |}{res}      1714           1           0          1          1
{txt}conditiong~p {c |}{res}      1834    6.444929    3.447125          1         12
{txt}charitygiv~W {c |}{res}      1822    3.789243    8.882511          0        200
{txt}charitycat~y {c |}{res}      1822    1.768386    .6905095          1          5
{txt}{hline 13}{c +}{hline 56}
{space 3}knowq1new {c |}{res}      1831    3.169853    1.061542          1          5
{txt}ineffectq2~w {c |}{res}      1828    3.584245    1.317647          1          5
{txt}knowconseq~w {c |}{res}      1832    3.456878    1.011294          1          5
{txt}conseqsq4new {c |}{res}      1827    4.030651    .8844165          1          5
{txt}knoweffect~w {c |}{res}      1831    3.174768    1.063059          1          5
{txt}{hline 13}{c +}{hline 56}
{space 1}appropq6new {c |}{res}      1827    1.863711    .9997437          1          5
{txt}emotionq7new {c |}{res}      1830    2.960656     .826425          1          4
{txt}{space 3}feelq8new {c |}{res}      1830     1.91694    .8441659          1          5
{txt}feelconseq~w {c |}{res}      1826    3.776561    .9619719          1          5
{txt}feeleffect~w {c |}{res}      1825    3.598356    1.032529          1          5
{txt}{hline 13}{c +}{hline 56}
participat~w {c |}{res}      1828     3.02954    1.137605          1          5
{txt}supportq12~w {c |}{res}      1832    3.532751      1.1577          1          5
{txt}genderq14new {c |}{res}      1823     .621503    .4851455          0          1
{txt}influenceq~w {c |}{res}      1830    2.105464    .7344694          1          4
{txt}charityeff~w {c |}{res}      1829    3.686167    .8477864          1          5
{txt}{hline 13}{c +}{hline 56}
{space 6}action {c |}{res}      1834    .3642312    .4813452          0          1

{com}. * * * Model 1: * * *

. ologit  appropq6new  c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2223.8879}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2178.0137}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2177.8218}  
Iteration 3:{space 3}log pseudolikelihood = {res:-2177.8218}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1797
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}     93.47
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-2177.8218{txt}{col 51}Pseudo R2{col 67}= {res}    0.0207

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1} appropq6new{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2}-.4970906{col 26}{space 2}  .191839{col 37}{space 1}   -2.59{col 46}{space 3}0.010{col 54}{space 4}-.8730882{col 67}{space 3}-.1210931
{txt}{space 10}c3 {c |}{col 14}{res}{space 2} -1.06062{col 26}{space 2} .2081096{col 37}{space 1}   -5.10{col 46}{space 3}0.000{col 54}{space 4}-1.468507{col 67}{space 3}-.6527325
{txt}{space 10}c4 {c |}{col 14}{res}{space 2}-1.290049{col 26}{space 2} .2215743{col 37}{space 1}   -5.82{col 46}{space 3}0.000{col 54}{space 4}-1.724327{col 67}{space 3}-.8557714
{txt}{space 10}c5 {c |}{col 14}{res}{space 2}-.1651098{col 26}{space 2} .1947756{col 37}{space 1}   -0.85{col 46}{space 3}0.397{col 54}{space 4}-.5468629{col 67}{space 3} .2166433
{txt}{space 10}c6 {c |}{col 14}{res}{space 2}-.8350721{col 26}{space 2} .2103893{col 37}{space 1}   -3.97{col 46}{space 3}0.000{col 54}{space 4}-1.247428{col 67}{space 3}-.4227167
{txt}{space 10}c7 {c |}{col 14}{res}{space 2}-.9845577{col 26}{space 2} .2040998{col 37}{space 1}   -4.82{col 46}{space 3}0.000{col 54}{space 4}-1.384586{col 67}{space 3}-.5845294
{txt}{space 10}c8 {c |}{col 14}{res}{space 2} -.551372{col 26}{space 2} .2037906{col 37}{space 1}   -2.71{col 46}{space 3}0.007{col 54}{space 4}-.9507942{col 67}{space 3}-.1519498
{txt}{space 10}c9 {c |}{col 14}{res}{space 2}-.8278005{col 26}{space 2} .2179533{col 37}{space 1}   -3.80{col 46}{space 3}0.000{col 54}{space 4}-1.254981{col 67}{space 3}-.4006198
{txt}{space 9}c10 {c |}{col 14}{res}{space 2}-1.058835{col 26}{space 2} .2237832{col 37}{space 1}   -4.73{col 46}{space 3}0.000{col 54}{space 4}-1.497442{col 67}{space 3}-.6202277
{txt}{space 9}c11 {c |}{col 14}{res}{space 2}-.6535772{col 26}{space 2} .1973983{col 37}{space 1}   -3.31{col 46}{space 3}0.001{col 54}{space 4}-1.040471{col 67}{space 3}-.2666836
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} -.930726{col 26}{space 2} .2094698{col 37}{space 1}   -4.44{col 46}{space 3}0.000{col 54}{space 4}-1.341279{col 67}{space 3}-.5201729
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2} .0008807{col 26}{space 2} .0042449{col 37}{space 1}    0.21{col 46}{space 3}0.836{col 54}{space 4} -.007439{col 67}{space 3} .0092005
{txt}genderq14new {c |}{col 14}{res}{space 2} .2596521{col 26}{space 2} .0947176{col 37}{space 1}    2.74{col 46}{space 3}0.006{col 54}{space 4} .0740091{col 67}{space 3} .4452951
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2} .0225502{col 26}{space 2} .0365197{col 37}{space 1}    0.62{col 46}{space 3}0.537{col 54}{space 4}-.0490271{col 67}{space 3} .0941275
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2}-.1652967{col 26}{space 2} .0412805{col 37}{space 1}   -4.00{col 46}{space 3}0.000{col 54}{space 4}-.2462049{col 67}{space 3}-.0843884
{txt}influenceq~w {c |}{col 14}{res}{space 2} .0916566{col 26}{space 2} .0669152{col 37}{space 1}    1.37{col 46}{space 3}0.171{col 54}{space 4}-.0394947{col 67}{space 3} .2228079
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2} -1.06819{col 26}{space 2} .2920288{col 54}{space 4}-1.640556{col 67}{space 3}-.4958246
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2}  .492515{col 26}{space 2} .2905952{col 54}{space 4}-.0770411{col 67}{space 3} 1.062071
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2} 1.643402{col 26}{space 2} .2882627{col 54}{space 4} 1.078417{col 67}{space 3} 2.208386
{col 1}{txt}       /cut4{col 14}{c |}{res}{space 2} 3.039174{col 26}{space 2} .3052168{col 54}{space 4}  2.44096{col 67}{space 3} 3.637388
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. * * * Predicted Probabilities (run after regression model): * * *

. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean) 

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.2752{col 32}{txt}[{res} 0.2186{txt},{res}{col 44} 0.3319{txt}]
     Pr(y=2|x):{res}{col 22} 0.3687{col 32}{txt}[{res} 0.3433{txt},{res}{col 44} 0.3941{txt}]
     Pr(y=3|x):{res}{col 22} 0.2072{col 32}{txt}[{res} 0.1711{txt},{res}{col 44} 0.2433{txt}]
     Pr(y=4|x):{res}{col 22} 0.1074{col 32}{txt}[{res} 0.0783{txt},{res}{col 44} 0.1364{txt}]
     Pr(y=5|x):{res}{col 22} 0.0415{col 32}{txt}[{res} 0.0259{txt},{res}{col 44} 0.0572{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=1 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.3844{col 32}{txt}[{res} 0.3181{txt},{res}{col 44} 0.4506{txt}]
     Pr(y=2|x):{res}{col 22} 0.3639{col 32}{txt}[{res} 0.3368{txt},{res}{col 44} 0.3911{txt}]
     Pr(y=3|x):{res}{col 22} 0.1555{col 32}{txt}[{res} 0.1234{txt},{res}{col 44} 0.1876{txt}]
     Pr(y=4|x):{res}{col 22} 0.0705{col 32}{txt}[{res} 0.0500{txt},{res}{col 44} 0.0910{txt}]
     Pr(y=5|x):{res}{col 22} 0.0257{col 32}{txt}[{res} 0.0154{txt},{res}{col 44} 0.0359{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           1             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=1 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.5231{col 32}{txt}[{res} 0.4436{txt},{res}{col 44} 0.6026{txt}]
     Pr(y=2|x):{res}{col 22} 0.3162{col 32}{txt}[{res} 0.2755{txt},{res}{col 44} 0.3570{txt}]
     Pr(y=3|x):{res}{col 22} 0.1036{col 32}{txt}[{res} 0.0758{txt},{res}{col 44} 0.1314{txt}]
     Pr(y=4|x):{res}{col 22} 0.0423{col 32}{txt}[{res} 0.0277{txt},{res}{col 44} 0.0569{txt}]
     Pr(y=5|x):{res}{col 22} 0.0148{col 32}{txt}[{res} 0.0081{txt},{res}{col 44} 0.0214{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             1             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=1 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.5798{col 32}{txt}[{res} 0.4956{txt},{res}{col 44} 0.6640{txt}]
     Pr(y=2|x):{res}{col 22} 0.2881{col 32}{txt}[{res} 0.2413{txt},{res}{col 44} 0.3349{txt}]
     Pr(y=3|x):{res}{col 22} 0.0862{col 32}{txt}[{res} 0.0599{txt},{res}{col 44} 0.1124{txt}]
     Pr(y=4|x):{res}{col 22} 0.0342{col 32}{txt}[{res} 0.0212{txt},{res}{col 44} 0.0471{txt}]
     Pr(y=5|x):{res}{col 22} 0.0118{col 32}{txt}[{res} 0.0063{txt},{res}{col 44} 0.0173{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             1             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=1 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.3094{col 32}{txt}[{res} 0.2482{txt},{res}{col 44} 0.3705{txt}]
     Pr(y=2|x):{res}{col 22} 0.3715{col 32}{txt}[{res} 0.3472{txt},{res}{col 44} 0.3958{txt}]
     Pr(y=3|x):{res}{col 22} 0.1900{col 32}{txt}[{res} 0.1549{txt},{res}{col 44} 0.2251{txt}]
     Pr(y=4|x):{res}{col 22} 0.0937{col 32}{txt}[{res} 0.0673{txt},{res}{col 44} 0.1202{txt}]
     Pr(y=5|x):{res}{col 22} 0.0354{col 32}{txt}[{res} 0.0214{txt},{res}{col 44} 0.0494{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             1             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=1 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.4668{col 32}{txt}[{res} 0.3859{txt},{res}{col 44} 0.5476{txt}]
     Pr(y=2|x):{res}{col 22} 0.3398{col 32}{txt}[{res} 0.3037{txt},{res}{col 44} 0.3758{txt}]
     Pr(y=3|x):{res}{col 22} 0.1229{col 32}{txt}[{res} 0.0913{txt},{res}{col 44} 0.1546{txt}]
     Pr(y=4|x):{res}{col 22} 0.0521{col 32}{txt}[{res} 0.0340{txt},{res}{col 44} 0.0702{txt}]
     Pr(y=5|x):{res}{col 22} 0.0184{col 32}{txt}[{res} 0.0101{txt},{res}{col 44} 0.0268{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             1             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=1 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.5041{col 32}{txt}[{res} 0.4268{txt},{res}{col 44} 0.5814{txt}]
     Pr(y=2|x):{res}{col 22} 0.3247{col 32}{txt}[{res} 0.2863{txt},{res}{col 44} 0.3631{txt}]
     Pr(y=3|x):{res}{col 22} 0.1099{col 32}{txt}[{res} 0.0813{txt},{res}{col 44} 0.1384{txt}]
     Pr(y=4|x):{res}{col 22} 0.0454{col 32}{txt}[{res} 0.0304{txt},{res}{col 44} 0.0604{txt}]
     Pr(y=5|x):{res}{col 22} 0.0159{col 32}{txt}[{res} 0.0090{txt},{res}{col 44} 0.0229{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             1             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=1 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.3973{col 32}{txt}[{res} 0.3238{txt},{res}{col 44} 0.4707{txt}]
     Pr(y=2|x):{res}{col 22} 0.3611{col 32}{txt}[{res} 0.3325{txt},{res}{col 44} 0.3898{txt}]
     Pr(y=3|x):{res}{col 22} 0.1500{col 32}{txt}[{res} 0.1159{txt},{res}{col 44} 0.1842{txt}]
     Pr(y=4|x):{res}{col 22} 0.0672{col 32}{txt}[{res} 0.0460{txt},{res}{col 44} 0.0884{txt}]
     Pr(y=5|x):{res}{col 22} 0.0243{col 32}{txt}[{res} 0.0141{txt},{res}{col 44} 0.0346{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             1

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=1 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.4650{col 32}{txt}[{res} 0.3786{txt},{res}{col 44} 0.5513{txt}]
     Pr(y=2|x):{res}{col 22} 0.3404{col 32}{txt}[{res} 0.3030{txt},{res}{col 44} 0.3778{txt}]
     Pr(y=3|x):{res}{col 22} 0.1236{col 32}{txt}[{res} 0.0896{txt},{res}{col 44} 0.1576{txt}]
     Pr(y=4|x):{res}{col 22} 0.0524{col 32}{txt}[{res} 0.0334{txt},{res}{col 44} 0.0715{txt}]
     Pr(y=5|x):{res}{col 22} 0.0186{col 32}{txt}[{res} 0.0099{txt},{res}{col 44} 0.0273{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           1             0             0             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=1 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.5227{col 32}{txt}[{res} 0.4343{txt},{res}{col 44} 0.6110{txt}]
     Pr(y=2|x):{res}{col 22} 0.3164{col 32}{txt}[{res} 0.2727{txt},{res}{col 44} 0.3601{txt}]
     Pr(y=3|x):{res}{col 22} 0.1037{col 32}{txt}[{res} 0.0729{txt},{res}{col 44} 0.1345{txt}]
     Pr(y=4|x):{res}{col 22} 0.0424{col 32}{txt}[{res} 0.0261{txt},{res}{col 44} 0.0587{txt}]
     Pr(y=5|x):{res}{col 22} 0.0148{col 32}{txt}[{res} 0.0078{txt},{res}{col 44} 0.0218{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             1             0             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=1 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.4220{col 32}{txt}[{res} 0.3520{txt},{res}{col 44} 0.4920{txt}]
     Pr(y=2|x):{res}{col 22} 0.3546{col 32}{txt}[{res} 0.3245{txt},{res}{col 44} 0.3848{txt}]
     Pr(y=3|x):{res}{col 22} 0.1400{col 32}{txt}[{res} 0.1086{txt},{res}{col 44} 0.1713{txt}]
     Pr(y=4|x):{res}{col 22} 0.0614{col 32}{txt}[{res} 0.0428{txt},{res}{col 44} 0.0799{txt}]
     Pr(y=5|x):{res}{col 22} 0.0220{col 32}{txt}[{res} 0.0132{txt},{res}{col 44} 0.0309{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             1             0     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=1 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}ologit{txt}: Predictions for {res}appropq6new

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
     Pr(y=1|x):{res}{col 22} 0.4906{col 32}{txt}[{res} 0.4105{txt},{res}{col 44} 0.5708{txt}]
     Pr(y=2|x):{res}{col 22} 0.3304{col 32}{txt}[{res} 0.2923{txt},{res}{col 44} 0.3684{txt}]
     Pr(y=3|x):{res}{col 22} 0.1145{col 32}{txt}[{res} 0.0841{txt},{res}{col 44} 0.1449{txt}]
     Pr(y=4|x):{res}{col 22} 0.0477{col 32}{txt}[{res} 0.0314{txt},{res}{col 44} 0.0640{txt}]
     Pr(y=5|x):{res}{col 22} 0.0168{col 32}{txt}[{res} 0.0094{txt},{res}{col 44} 0.0242{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             1     31.769616             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. * * * Wald�s Test (run after regression model): * * *

. test c2=c3

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c2 - [appropq6new]c3 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    7.34
{txt}{col 10}Prob > chi2 =  {res}  0.0068

{com}. test c2=c4

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c2 - [appropq6new]c4 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   12.81
{txt}{col 10}Prob > chi2 =  {res}  0.0003

{com}. test c2=c5

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c2 - [appropq6new]c5 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.88
{txt}{col 10}Prob > chi2 =  {res}  0.0899

{com}. test c2=c6

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c2 - [appropq6new]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.59
{txt}{col 10}Prob > chi2 =  {res}  0.1077

{com}. test c2=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c2 - [appropq6new]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    5.68
{txt}{col 10}Prob > chi2 =  {res}  0.0172

{com}. test c2=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c2 - [appropq6new]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.07
{txt}{col 10}Prob > chi2 =  {res}  0.7905

{com}. test c2=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c2 - [appropq6new]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.30
{txt}{col 10}Prob > chi2 =  {res}  0.1293

{com}. test c2=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c2 - [appropq6new]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    6.30
{txt}{col 10}Prob > chi2 =  {res}  0.0121

{com}. test c2=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c2 - [appropq6new]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.63
{txt}{col 10}Prob > chi2 =  {res}  0.4289

{com}. test c2=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c2 - [appropq6new]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    4.27
{txt}{col 10}Prob > chi2 =  {res}  0.0387

{com}. test c3=c4

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c3 - [appropq6new]c4 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.96
{txt}{col 10}Prob > chi2 =  {res}  0.3270

{com}. test c3=c5

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c3 - [appropq6new]c5 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   17.91
{txt}{col 10}Prob > chi2 =  {res}  0.0000

{com}. test c3=c6 

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c3 - [appropq6new]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.02
{txt}{col 10}Prob > chi2 =  {res}  0.3137

{com}. test c3=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c3 - [appropq6new]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.12
{txt}{col 10}Prob > chi2 =  {res}  0.7274

{com}. test c3=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c3 - [appropq6new]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    5.39
{txt}{col 10}Prob > chi2 =  {res}  0.0202

{com}. test c3=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c3 - [appropq6new]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.02
{txt}{col 10}Prob > chi2 =  {res}  0.3136

{com}. test c3=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c3 - [appropq6new]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.00
{txt}{col 10}Prob > chi2 =  {res}  0.9940

{com}. test c3=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c3 - [appropq6new]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    3.64
{txt}{col 10}Prob > chi2 =  {res}  0.0564

{com}. test c3=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c3 - [appropq6new]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.34
{txt}{col 10}Prob > chi2 =  {res}  0.5619

{com}. test c4=c5

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c4 - [appropq6new]c5 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   25.21
{txt}{col 10}Prob > chi2 =  {res}  0.0000

{com}. test c4=c6

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c4 - [appropq6new]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    3.72
{txt}{col 10}Prob > chi2 =  {res}  0.0537

{com}. test c4=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c4 - [appropq6new]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.76
{txt}{col 10}Prob > chi2 =  {res}  0.1849

{com}. test c4=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c4 - [appropq6new]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   10.22
{txt}{col 10}Prob > chi2 =  {res}  0.0014

{com}. test c4=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c4 - [appropq6new]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    3.63
{txt}{col 10}Prob > chi2 =  {res}  0.0566

{com}. test c4=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c4 - [appropq6new]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.88
{txt}{col 10}Prob > chi2 =  {res}  0.3488

{com}. test c4=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c4 - [appropq6new]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    7.99
{txt}{col 10}Prob > chi2 =  {res}  0.0047

{com}. test c4=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c4 - [appropq6new]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.34
{txt}{col 10}Prob > chi2 =  {res}  0.1257

{com}. test c5=c6

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c5 - [appropq6new]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    9.79
{txt}{col 10}Prob > chi2 =  {res}  0.0018

{com}. test c5=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c5 - [appropq6new]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   15.63
{txt}{col 10}Prob > chi2 =  {res}  0.0001

{com}. test c5=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c5 - [appropq6new]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    3.48
{txt}{col 10}Prob > chi2 =  {res}  0.0620

{com}. test c5=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c5 - [appropq6new]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    8.94
{txt}{col 10}Prob > chi2 =  {res}  0.0028

{com}. test c5=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c5 - [appropq6new]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   15.57
{txt}{col 10}Prob > chi2 =  {res}  0.0001

{com}. test c5=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c5 - [appropq6new]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    5.91
{txt}{col 10}Prob > chi2 =  {res}  0.0150

{com}. test c5=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c5 - [appropq6new]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}   12.91
{txt}{col 10}Prob > chi2 =  {res}  0.0003

{com}. test c6=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c6 - [appropq6new]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.46
{txt}{col 10}Prob > chi2 =  {res}  0.4980

{com}. test c6=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c6 - [appropq6new]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.65
{txt}{col 10}Prob > chi2 =  {res}  0.1984

{com}. test c6=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c6 - [appropq6new]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.00
{txt}{col 10}Prob > chi2 =  {res}  0.9750

{com}. test c6=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c6 - [appropq6new]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.89
{txt}{col 10}Prob > chi2 =  {res}  0.3464

{com}. test c6=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c6 - [appropq6new]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.72
{txt}{col 10}Prob > chi2 =  {res}  0.3977

{com}. test c6=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c6 - [appropq6new]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.18
{txt}{col 10}Prob > chi2 =  {res}  0.6699

{com}. test c7=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c7 - [appropq6new]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    4.04
{txt}{col 10}Prob > chi2 =  {res}  0.0444

{com}. test c7=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c7 - [appropq6new]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.47
{txt}{col 10}Prob > chi2 =  {res}  0.4908

{com}. test c7=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c7 - [appropq6new]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.10
{txt}{col 10}Prob > chi2 =  {res}  0.7491

{com}. test c7=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c7 - [appropq6new]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.49
{txt}{col 10}Prob > chi2 =  {res}  0.1146

{com}. test c7=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c7 - [appropq6new]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.06
{txt}{col 10}Prob > chi2 =  {res}  0.8066

{com}. test c8=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c8 - [appropq6new]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.47
{txt}{col 10}Prob > chi2 =  {res}  0.2260

{com}. test c8=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c8 - [appropq6new]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    4.73
{txt}{col 10}Prob > chi2 =  {res}  0.0297

{com}. test c8=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c8 - [appropq6new]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.24
{txt}{col 10}Prob > chi2 =  {res}  0.6238

{com}. test c8=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c8 - [appropq6new]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.98
{txt}{col 10}Prob > chi2 =  {res}  0.0843

{com}. test c9=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c9 - [appropq6new]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.90
{txt}{col 10}Prob > chi2 =  {res}  0.3440

{com}. test c9=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c9 - [appropq6new]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.61
{txt}{col 10}Prob > chi2 =  {res}  0.4333

{com}. test c9=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c9 - [appropq6new]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.20
{txt}{col 10}Prob > chi2 =  {res}  0.6566

{com}. test c10=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c10 - [appropq6new]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    3.17
{txt}{col 10}Prob > chi2 =  {res}  0.0752

{com}. test c10=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c10 - [appropq6new]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.29
{txt}{col 10}Prob > chi2 =  {res}  0.5886

{com}. test c11=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[appropq6new]c11 - [appropq6new]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.68
{txt}{col 10}Prob > chi2 =  {res}  0.1945

{com}. 
. 
. * * * Model 2: * * *

. logit agpetition c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1156.6781}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1125.3138}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1125.1388}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1125.1388}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      1802
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}     61.72
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1125.1388{txt}{col 51}Pseudo R2{col 67}= {res}    0.0273

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}agpetitio~21{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2} .4841207{col 26}{space 2} .2575513{col 37}{space 1}    1.88{col 46}{space 3}0.060{col 54}{space 4}-.0206705{col 67}{space 3}  .988912
{txt}{space 10}c3 {c |}{col 14}{res}{space 2} .6152452{col 26}{space 2} .2542026{col 37}{space 1}    2.42{col 46}{space 3}0.016{col 54}{space 4} .1170172{col 67}{space 3} 1.113473
{txt}{space 10}c4 {c |}{col 14}{res}{space 2} .3574032{col 26}{space 2} .2642493{col 37}{space 1}    1.35{col 46}{space 3}0.176{col 54}{space 4} -.160516{col 67}{space 3} .8753224
{txt}{space 10}c5 {c |}{col 14}{res}{space 2} .1923974{col 26}{space 2}  .261754{col 37}{space 1}    0.74{col 46}{space 3}0.462{col 54}{space 4} -.320631{col 67}{space 3} .7054258
{txt}{space 10}c6 {c |}{col 14}{res}{space 2} .7276883{col 26}{space 2} .2549752{col 37}{space 1}    2.85{col 46}{space 3}0.004{col 54}{space 4} .2279462{col 67}{space 3}  1.22743
{txt}{space 10}c7 {c |}{col 14}{res}{space 2}  .555663{col 26}{space 2} .2568488{col 37}{space 1}    2.16{col 46}{space 3}0.031{col 54}{space 4} .0522486{col 67}{space 3} 1.059077
{txt}{space 10}c8 {c |}{col 14}{res}{space 2}  .621226{col 26}{space 2} .2588257{col 37}{space 1}    2.40{col 46}{space 3}0.016{col 54}{space 4}  .113937{col 67}{space 3} 1.128515
{txt}{space 10}c9 {c |}{col 14}{res}{space 2} .5704612{col 26}{space 2} .2568097{col 37}{space 1}    2.22{col 46}{space 3}0.026{col 54}{space 4} .0671233{col 67}{space 3} 1.073799
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} .8213475{col 26}{space 2} .2514426{col 37}{space 1}    3.27{col 46}{space 3}0.001{col 54}{space 4} .3285291{col 67}{space 3} 1.314166
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} .5803489{col 26}{space 2} .2570241{col 37}{space 1}    2.26{col 46}{space 3}0.024{col 54}{space 4} .0765909{col 67}{space 3} 1.084107
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} .4546513{col 26}{space 2} .2573626{col 37}{space 1}    1.77{col 46}{space 3}0.077{col 54}{space 4}-.0497702{col 67}{space 3} .9590728
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2}-.0053826{col 26}{space 2} .0051489{col 37}{space 1}   -1.05{col 46}{space 3}0.296{col 54}{space 4}-.0154743{col 67}{space 3} .0047091
{txt}genderq14new {c |}{col 14}{res}{space 2}-.1273992{col 26}{space 2} .1082542{col 37}{space 1}   -1.18{col 46}{space 3}0.239{col 54}{space 4}-.3395736{col 67}{space 3} .0847751
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2}-.1571552{col 26}{space 2} .0393562{col 37}{space 1}   -3.99{col 46}{space 3}0.000{col 54}{space 4}-.2342918{col 67}{space 3}-.0800185
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .1269911{col 26}{space 2}  .046938{col 37}{space 1}    2.71{col 46}{space 3}0.007{col 54}{space 4} .0349944{col 67}{space 3} .2189879
{txt}influenceq~w {c |}{col 14}{res}{space 2}  .340358{col 26}{space 2} .0682363{col 37}{space 1}    4.99{col 46}{space 3}0.000{col 54}{space 4} .2066173{col 67}{space 3} .4740988
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.495597{col 26}{space 2} .3460718{col 37}{space 1}   -4.32{col 46}{space 3}0.000{col 54}{space 4}-2.173885{col 67}{space 3}-.8173085
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. * * *Predicted Probabilities (run after regression model): * * *

. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean) 

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.2255{col 32}{txt}[{res} 0.1594{txt},{res}{col 44} 0.2916{txt}]
  Pr(y=0|x):{res}{col 22} 0.7745{col 32}{txt}[{res} 0.7084{txt},{res}{col 44} 0.8406{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=1 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3209{col 32}{txt}[{res} 0.2444{txt},{res}{col 44} 0.3973{txt}]
  Pr(y=0|x):{res}{col 22} 0.6791{col 32}{txt}[{res} 0.6027{txt},{res}{col 44} 0.7556{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           1             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=1 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3501{col 32}{txt}[{res} 0.2720{txt},{res}{col 44} 0.4282{txt}]
  Pr(y=0|x):{res}{col 22} 0.6499{col 32}{txt}[{res} 0.5718{txt},{res}{col 44} 0.7280{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             1             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=1 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.2939{col 32}{txt}[{res} 0.2167{txt},{res}{col 44} 0.3711{txt}]
  Pr(y=0|x):{res}{col 22} 0.7061{col 32}{txt}[{res} 0.6289{txt},{res}{col 44} 0.7833{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             1             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=1 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.2609{col 32}{txt}[{res} 0.1904{txt},{res}{col 44} 0.3313{txt}]
  Pr(y=0|x):{res}{col 22} 0.7391{col 32}{txt}[{res} 0.6687{txt},{res}{col 44} 0.8096{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             1             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=1 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3761{col 32}{txt}[{res} 0.2946{txt},{res}{col 44} 0.4575{txt}]
  Pr(y=0|x):{res}{col 22} 0.6239{col 32}{txt}[{res} 0.5425{txt},{res}{col 44} 0.7054{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             1             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=1 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3367{col 32}{txt}[{res} 0.2574{txt},{res}{col 44} 0.4159{txt}]
  Pr(y=0|x):{res}{col 22} 0.6633{col 32}{txt}[{res} 0.5841{txt},{res}{col 44} 0.7426{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             1             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=1 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3514{col 32}{txt}[{res} 0.2705{txt},{res}{col 44} 0.4324{txt}]
  Pr(y=0|x):{res}{col 22} 0.6486{col 32}{txt}[{res} 0.5676{txt},{res}{col 44} 0.7295{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             1

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=1 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3400{col 32}{txt}[{res} 0.2611{txt},{res}{col 44} 0.4188{txt}]
  Pr(y=0|x):{res}{col 22} 0.6600{col 32}{txt}[{res} 0.5812{txt},{res}{col 44} 0.7389{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           1             0             0             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=1 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3983{col 32}{txt}[{res} 0.3179{txt},{res}{col 44} 0.4787{txt}]
  Pr(y=0|x):{res}{col 22} 0.6017{col 32}{txt}[{res} 0.5213{txt},{res}{col 44} 0.6821{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             1             0             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=1 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3422{col 32}{txt}[{res} 0.2636{txt},{res}{col 44} 0.4207{txt}]
  Pr(y=0|x):{res}{col 22} 0.6578{col 32}{txt}[{res} 0.5793{txt},{res}{col 44} 0.7364{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             1             0     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=1 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}agpetitionq21

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3145{col 32}{txt}[{res} 0.2384{txt},{res}{col 44} 0.3905{txt}]
  Pr(y=0|x):{res}{col 22} 0.6855{col 32}{txt}[{res} 0.6095{txt},{res}{col 44} 0.7616{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             1     31.765261             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. * * *Wald�s Test (run after regression model): * * *

. test c2=c3

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c2 - [agpetitionq21]c3 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.29
{txt}{col 10}Prob > chi2 =  {res}  0.5910

{com}. test c2=c4

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c2 - [agpetitionq21]c4 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.25
{txt}{col 10}Prob > chi2 =  {res}  0.6179

{com}. test c2=c5

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c2 - [agpetitionq21]c5 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.34
{txt}{col 10}Prob > chi2 =  {res}  0.2474

{com}. test c2=c6

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c2 - [agpetitionq21]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.99
{txt}{col 10}Prob > chi2 =  {res}  0.3192

{com}. test c2=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c2 - [agpetitionq21]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.08
{txt}{col 10}Prob > chi2 =  {res}  0.7719

{com}. test c2=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c2 - [agpetitionq21]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.30
{txt}{col 10}Prob > chi2 =  {res}  0.5810

{com}. test c2=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c2 - [agpetitionq21]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.12
{txt}{col 10}Prob > chi2 =  {res}  0.7260

{com}. test c2=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c2 - [agpetitionq21]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.97
{txt}{col 10}Prob > chi2 =  {res}  0.1609

{com}. test c2=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c2 - [agpetitionq21]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.15
{txt}{col 10}Prob > chi2 =  {res}  0.6966

{com}. test c2=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c2 - [agpetitionq21]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.01
{txt}{col 10}Prob > chi2 =  {res}  0.9050

{com}. test c3=c4

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c3 - [agpetitionq21]c4 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.06
{txt}{col 10}Prob > chi2 =  {res}  0.3036

{com}. test c3=c5

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c3 - [agpetitionq21]c5 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.89
{txt}{col 10}Prob > chi2 =  {res}  0.0891

{com}. test c3=c6 

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c3 - [agpetitionq21]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.22
{txt}{col 10}Prob > chi2 =  {res}  0.6414

{com}. test c3=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c3 - [agpetitionq21]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.06
{txt}{col 10}Prob > chi2 =  {res}  0.8064

{com}. test c3=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c3 - [agpetitionq21]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.00
{txt}{col 10}Prob > chi2 =  {res}  0.9805

{com}. test c3=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c3 - [agpetitionq21]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.03
{txt}{col 10}Prob > chi2 =  {res}  0.8537

{com}. test c3=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c3 - [agpetitionq21]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.75
{txt}{col 10}Prob > chi2 =  {res}  0.3849

{com}. test c3=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c3 - [agpetitionq21]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.02
{txt}{col 10}Prob > chi2 =  {res}  0.8861

{com}. test c3=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c3 - [agpetitionq21]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.44
{txt}{col 10}Prob > chi2 =  {res}  0.5091

{com}. test c4=c5

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c4 - [agpetitionq21]c5 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.41
{txt}{col 10}Prob > chi2 =  {res}  0.5241

{com}. test c4=c6

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c4 - [agpetitionq21]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.17
{txt}{col 10}Prob > chi2 =  {res}  0.1411

{com}. test c4=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c4 - [agpetitionq21]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.61
{txt}{col 10}Prob > chi2 =  {res}  0.4342

{com}. test c4=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c4 - [agpetitionq21]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.07
{txt}{col 10}Prob > chi2 =  {res}  0.3013

{com}. test c4=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c4 - [agpetitionq21]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.71
{txt}{col 10}Prob > chi2 =  {res}  0.3999

{com}. test c4=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c4 - [agpetitionq21]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    3.52
{txt}{col 10}Prob > chi2 =  {res}  0.0608

{com}. test c4=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c4 - [agpetitionq21]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.77
{txt}{col 10}Prob > chi2 =  {res}  0.3796

{com}. test c4=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c4 - [agpetitionq21]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.15
{txt}{col 10}Prob > chi2 =  {res}  0.7013

{com}. test c5=c6

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c5 - [agpetitionq21]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    4.62
{txt}{col 10}Prob > chi2 =  {res}  0.0316

{com}. test c5=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c5 - [agpetitionq21]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.09
{txt}{col 10}Prob > chi2 =  {res}  0.1484

{com}. test c5=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c5 - [agpetitionq21]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.86
{txt}{col 10}Prob > chi2 =  {res}  0.0907

{com}. test c5=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c5 - [agpetitionq21]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.26
{txt}{col 10}Prob > chi2 =  {res}  0.1325

{com}. test c5=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c5 - [agpetitionq21]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    6.55
{txt}{col 10}Prob > chi2 =  {res}  0.0105

{com}. test c5=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c5 - [agpetitionq21]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.38
{txt}{col 10}Prob > chi2 =  {res}  0.1229

{com}. test c5=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c5 - [agpetitionq21]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.09
{txt}{col 10}Prob > chi2 =  {res}  0.2971

{com}. test c6=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c6 - [agpetitionq21]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.50
{txt}{col 10}Prob > chi2 =  {res}  0.4808

{com}. test c6=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c6 - [agpetitionq21]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.19
{txt}{col 10}Prob > chi2 =  {res}  0.6656

{com}. test c6=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c6 - [agpetitionq21]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.42
{txt}{col 10}Prob > chi2 =  {res}  0.5190

{com}. test c6=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c6 - [agpetitionq21]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.16
{txt}{col 10}Prob > chi2 =  {res}  0.6933

{com}. test c6=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c6 - [agpetitionq21]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.36
{txt}{col 10}Prob > chi2 =  {res}  0.5459

{com}. test c6=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c6 - [agpetitionq21]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.25
{txt}{col 10}Prob > chi2 =  {res}  0.2630

{com}. test c7=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c7 - [agpetitionq21]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.07
{txt}{col 10}Prob > chi2 =  {res}  0.7917

{com}. test c7=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c7 - [agpetitionq21]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.00
{txt}{col 10}Prob > chi2 =  {res}  0.9520

{com}. test c7=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c7 - [agpetitionq21]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.22
{txt}{col 10}Prob > chi2 =  {res}  0.2686

{com}. test c7=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c7 - [agpetitionq21]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.01
{txt}{col 10}Prob > chi2 =  {res}  0.9202

{com}. test c7=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c7 - [agpetitionq21]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.17
{txt}{col 10}Prob > chi2 =  {res}  0.6818

{com}. test c8=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c8 - [agpetitionq21]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.04
{txt}{col 10}Prob > chi2 =  {res}  0.8375

{com}. test c8=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c8 - [agpetitionq21]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.69
{txt}{col 10}Prob > chi2 =  {res}  0.4078

{com}. test c8=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c8 - [agpetitionq21]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.03
{txt}{col 10}Prob > chi2 =  {res}  0.8691

{com}. test c8=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c8 - [agpetitionq21]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.45
{txt}{col 10}Prob > chi2 =  {res}  0.5017

{com}. test c9=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c9 - [agpetitionq21]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.10
{txt}{col 10}Prob > chi2 =  {res}  0.2951

{com}. test c9=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c9 - [agpetitionq21]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.00
{txt}{col 10}Prob > chi2 =  {res}  0.9680

{com}. test c9=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c9 - [agpetitionq21]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.22
{txt}{col 10}Prob > chi2 =  {res}  0.6379

{com}. test c10=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c10 - [agpetitionq21]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.01
{txt}{col 10}Prob > chi2 =  {res}  0.3155

{com}. test c10=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c10 - [agpetitionq21]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.34
{txt}{col 10}Prob > chi2 =  {res}  0.1265

{com}. test c11=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[agpetitionq21]c11 - [agpetitionq21]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.26
{txt}{col 10}Prob > chi2 =  {res}  0.6100

{com}. 
. * * *Model 3: * * *

. logit unpetition c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-1159.5248}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1126.0838}  
Iteration 2:{space 3}log pseudolikelihood = {res:-1125.8486}  
Iteration 3:{space 3}log pseudolikelihood = {res:-1125.8485}  
Iteration 4:{space 3}log pseudolikelihood = {res:-1125.8485}  
{res}
{txt}Logistic regression{col 51}Number of obs{col 67}= {res}      1798
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}     65.04
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-1125.8485{txt}{col 51}Pseudo R2{col 67}= {res}    0.0290

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}unpetitio~22{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2} .5360215{col 26}{space 2} .2633712{col 37}{space 1}    2.04{col 46}{space 3}0.042{col 54}{space 4} .0198235{col 67}{space 3} 1.052219
{txt}{space 10}c3 {c |}{col 14}{res}{space 2} .7812282{col 26}{space 2} .2571212{col 37}{space 1}    3.04{col 46}{space 3}0.002{col 54}{space 4}   .27728{col 67}{space 3} 1.285176
{txt}{space 10}c4 {c |}{col 14}{res}{space 2} .6385708{col 26}{space 2} .2660884{col 37}{space 1}    2.40{col 46}{space 3}0.016{col 54}{space 4} .1170471{col 67}{space 3} 1.160094
{txt}{space 10}c5 {c |}{col 14}{res}{space 2} .3922293{col 26}{space 2} .2643883{col 37}{space 1}    1.48{col 46}{space 3}0.138{col 54}{space 4}-.1259621{col 67}{space 3} .9104208
{txt}{space 10}c6 {c |}{col 14}{res}{space 2}  .865342{col 26}{space 2} .2593157{col 37}{space 1}    3.34{col 46}{space 3}0.001{col 54}{space 4} .3570927{col 67}{space 3} 1.373591
{txt}{space 10}c7 {c |}{col 14}{res}{space 2} .6140991{col 26}{space 2} .2631123{col 37}{space 1}    2.33{col 46}{space 3}0.020{col 54}{space 4} .0984084{col 67}{space 3}  1.12979
{txt}{space 10}c8 {c |}{col 14}{res}{space 2}  .666003{col 26}{space 2} .2649995{col 37}{space 1}    2.51{col 46}{space 3}0.012{col 54}{space 4} .1466134{col 67}{space 3} 1.185393
{txt}{space 10}c9 {c |}{col 14}{res}{space 2}  .702564{col 26}{space 2} .2615988{col 37}{space 1}    2.69{col 46}{space 3}0.007{col 54}{space 4} .1898399{col 67}{space 3} 1.215288
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} .9557461{col 26}{space 2} .2564634{col 37}{space 1}    3.73{col 46}{space 3}0.000{col 54}{space 4}  .453087{col 67}{space 3} 1.458405
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} .7638936{col 26}{space 2} .2607835{col 37}{space 1}    2.93{col 46}{space 3}0.003{col 54}{space 4} .2527673{col 67}{space 3}  1.27502
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} .6282021{col 26}{space 2} .2611077{col 37}{space 1}    2.41{col 46}{space 3}0.016{col 54}{space 4} .1164404{col 67}{space 3} 1.139964
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2}-.0011566{col 26}{space 2} .0050716{col 37}{space 1}   -0.23{col 46}{space 3}0.820{col 54}{space 4}-.0110967{col 67}{space 3} .0087836
{txt}genderq14new {c |}{col 14}{res}{space 2}-.2313185{col 26}{space 2} .1079906{col 37}{space 1}   -2.14{col 46}{space 3}0.032{col 54}{space 4}-.4429763{col 67}{space 3}-.0196607
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2} -.139699{col 26}{space 2}  .039021{col 37}{space 1}   -3.58{col 46}{space 3}0.000{col 54}{space 4}-.2161787{col 67}{space 3}-.0632192
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .1115554{col 26}{space 2} .0464886{col 37}{space 1}    2.40{col 46}{space 3}0.016{col 54}{space 4} .0204394{col 67}{space 3} .2026714
{txt}influenceq~w {c |}{col 14}{res}{space 2}  .359879{col 26}{space 2} .0682841{col 37}{space 1}    5.27{col 46}{space 3}0.000{col 54}{space 4} .2260446{col 67}{space 3} .4937134
{txt}{space 7}_cons {c |}{col 14}{res}{space 2}-1.728627{col 26}{space 2} .3461686{col 37}{space 1}   -4.99{col 46}{space 3}0.000{col 54}{space 4}-2.407105{col 67}{space 3}-1.050149
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. * * *Predicted Probabilities (run after regression model): * * *

. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean) 

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.1995{col 32}{txt}[{res} 0.1371{txt},{res}{col 44} 0.2619{txt}]
  Pr(y=0|x):{res}{col 22} 0.8005{col 32}{txt}[{res} 0.7381{txt},{res}{col 44} 0.8629{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=1 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.2987{col 32}{txt}[{res} 0.2247{txt},{res}{col 44} 0.3727{txt}]
  Pr(y=0|x):{res}{col 22} 0.7013{col 32}{txt}[{res} 0.6273{txt},{res}{col 44} 0.7753{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           1             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=1 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3525{col 32}{txt}[{res} 0.2754{txt},{res}{col 44} 0.4296{txt}]
  Pr(y=0|x):{res}{col 22} 0.6475{col 32}{txt}[{res} 0.5704{txt},{res}{col 44} 0.7246{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             1             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=1 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3206{col 32}{txt}[{res} 0.2413{txt},{res}{col 44} 0.4000{txt}]
  Pr(y=0|x):{res}{col 22} 0.6794{col 32}{txt}[{res} 0.6000{txt},{res}{col 44} 0.7587{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             1             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=1 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.2695{col 32}{txt}[{res} 0.1988{txt},{res}{col 44} 0.3401{txt}]
  Pr(y=0|x):{res}{col 22} 0.7305{col 32}{txt}[{res} 0.6599{txt},{res}{col 44} 0.8012{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             1             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=1 c7=0 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3719{col 32}{txt}[{res} 0.2912{txt},{res}{col 44} 0.4525{txt}]
  Pr(y=0|x):{res}{col 22} 0.6281{col 32}{txt}[{res} 0.5475{txt},{res}{col 44} 0.7088{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             1             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=1 c8=0 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3153{col 32}{txt}[{res} 0.2375{txt},{res}{col 44} 0.3931{txt}]
  Pr(y=0|x):{res}{col 22} 0.6847{col 32}{txt}[{res} 0.6069{txt},{res}{col 44} 0.7625{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             1             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=1 c9=0 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3266{col 32}{txt}[{res} 0.2475{txt},{res}{col 44} 0.4057{txt}]
  Pr(y=0|x):{res}{col 22} 0.6734{col 32}{txt}[{res} 0.5943{txt},{res}{col 44} 0.7525{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             1

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=1 c10=0 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3347{col 32}{txt}[{res} 0.2565{txt},{res}{col 44} 0.4130{txt}]
  Pr(y=0|x):{res}{col 22} 0.6653{col 32}{txt}[{res} 0.5870{txt},{res}{col 44} 0.7435{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           1             0             0             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=1 c11=0 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3932{col 32}{txt}[{res} 0.3130{txt},{res}{col 44} 0.4735{txt}]
  Pr(y=0|x):{res}{col 22} 0.6068{col 32}{txt}[{res} 0.5265{txt},{res}{col 44} 0.6870{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             1             0             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=1 c12=0 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3485{col 32}{txt}[{res} 0.2698{txt},{res}{col 44} 0.4272{txt}]
  Pr(y=0|x):{res}{col 22} 0.6515{col 32}{txt}[{res} 0.5728{txt},{res}{col 44} 0.7302{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             1             0     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. prvalue, x(c2=0 c3=0 c4=0 c5=0 c6=0 c7=0 c8=0 c9=0 c10=0 c11=0 c12=1 genderq14new=1 educq15=4 newsq16=4 influenceq18new=2) rest(mean)

{res}logit{txt}: Predictions for {res}unpetitionq22

{txt}Confidence intervals by delta method

{col 32} 95% Conf. Interval
  Pr(y=1|x):{res}{col 22} 0.3184{col 32}{txt}[{res} 0.2424{txt},{res}{col 44} 0.3944{txt}]
  Pr(y=0|x):{res}{col 22} 0.6816{col 32}{txt}[{res} 0.6056{txt},{res}{col 44} 0.7576{txt}]

              c2            c3            c4            c5            c6            c7            c8
x=  {res}           0             0             0             0             0             0             0

    {txt}          c9           c10           c11           c12        ageq13  genderq14new       educq15
x=  {res}           0             0             0             1     31.727475             1             4

    {txt}     newsq16  influenceq~w
x=  {res}           4             2

{com}. * * *Wald�s Test (run after regression model): * * *

. test c2=c3

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c2 - [unpetitionq22]c3 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.02
{txt}{col 10}Prob > chi2 =  {res}  0.3133

{com}. test c2=c4

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c2 - [unpetitionq22]c4 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.17
{txt}{col 10}Prob > chi2 =  {res}  0.6842

{com}. test c2=c5

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c2 - [unpetitionq22]c5 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.33
{txt}{col 10}Prob > chi2 =  {res}  0.5668

{com}. test c2=c6

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c2 - [unpetitionq22]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.81
{txt}{col 10}Prob > chi2 =  {res}  0.1784

{com}. test c2=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c2 - [unpetitionq22]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.10
{txt}{col 10}Prob > chi2 =  {res}  0.7545

{com}. test c2=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c2 - [unpetitionq22]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.27
{txt}{col 10}Prob > chi2 =  {res}  0.6045

{com}. test c2=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c2 - [unpetitionq22]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.45
{txt}{col 10}Prob > chi2 =  {res}  0.5009

{com}. test c2=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c2 - [unpetitionq22]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    3.02
{txt}{col 10}Prob > chi2 =  {res}  0.0824

{com}. test c2=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c2 - [unpetitionq22]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.85
{txt}{col 10}Prob > chi2 =  {res}  0.3552

{com}. test c2=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c2 - [unpetitionq22]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.14
{txt}{col 10}Prob > chi2 =  {res}  0.7088

{com}. test c3=c4

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c3 - [unpetitionq22]c4 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.34
{txt}{col 10}Prob > chi2 =  {res}  0.5617

{com}. test c3=c5

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c3 - [unpetitionq22]c5 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.53
{txt}{col 10}Prob > chi2 =  {res}  0.1117

{com}. test c3=c6 

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c3 - [unpetitionq22]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.12
{txt}{col 10}Prob > chi2 =  {res}  0.7247

{com}. test c3=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c3 - [unpetitionq22]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.47
{txt}{col 10}Prob > chi2 =  {res}  0.4916

{com}. test c3=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c3 - [unpetitionq22]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.22
{txt}{col 10}Prob > chi2 =  {res}  0.6376

{com}. test c3=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c3 - [unpetitionq22]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.11
{txt}{col 10}Prob > chi2 =  {res}  0.7442

{com}. test c3=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c3 - [unpetitionq22]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.55
{txt}{col 10}Prob > chi2 =  {res}  0.4585

{com}. test c3=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c3 - [unpetitionq22]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.01
{txt}{col 10}Prob > chi2 =  {res}  0.9425

{com}. test c3=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c3 - [unpetitionq22]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.41
{txt}{col 10}Prob > chi2 =  {res}  0.5243

{com}. test c4=c5

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c4 - [unpetitionq22]c5 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.94
{txt}{col 10}Prob > chi2 =  {res}  0.3320

{com}. test c4=c6

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c4 - [unpetitionq22]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.83
{txt}{col 10}Prob > chi2 =  {res}  0.3609

{com}. test c4=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c4 - [unpetitionq22]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.01
{txt}{col 10}Prob > chi2 =  {res}  0.9228

{com}. test c4=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c4 - [unpetitionq22]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.01
{txt}{col 10}Prob > chi2 =  {res}  0.9140

{com}. test c4=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c4 - [unpetitionq22]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.07
{txt}{col 10}Prob > chi2 =  {res}  0.7983

{com}. test c4=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c4 - [unpetitionq22]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.68
{txt}{col 10}Prob > chi2 =  {res}  0.1949

{com}. test c4=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c4 - [unpetitionq22]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.25
{txt}{col 10}Prob > chi2 =  {res}  0.6159

{com}. test c4=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c4 - [unpetitionq22]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.00
{txt}{col 10}Prob > chi2 =  {res}  0.9669

{com}. test c5=c6

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c5 - [unpetitionq22]c6 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    3.69
{txt}{col 10}Prob > chi2 =  {res}  0.0547

{com}. test c5=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c5 - [unpetitionq22]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.78
{txt}{col 10}Prob > chi2 =  {res}  0.3765

{com}. test c5=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c5 - [unpetitionq22]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.17
{txt}{col 10}Prob > chi2 =  {res}  0.2787

{com}. test c5=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c5 - [unpetitionq22]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.55
{txt}{col 10}Prob > chi2 =  {res}  0.2131

{com}. test c5=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c5 - [unpetitionq22]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    5.35
{txt}{col 10}Prob > chi2 =  {res}  0.0207

{com}. test c5=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c5 - [unpetitionq22]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    2.24
{txt}{col 10}Prob > chi2 =  {res}  0.1341

{com}. test c5=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c5 - [unpetitionq22]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.90
{txt}{col 10}Prob > chi2 =  {res}  0.3419

{com}. test c6=c7

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c6 - [unpetitionq22]c7 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.05
{txt}{col 10}Prob > chi2 =  {res}  0.3055

{com}. test c6=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c6 - [unpetitionq22]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.65
{txt}{col 10}Prob > chi2 =  {res}  0.4201

{com}. test c6=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c6 - [unpetitionq22]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.45
{txt}{col 10}Prob > chi2 =  {res}  0.5036

{com}. test c6=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c6 - [unpetitionq22]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.15
{txt}{col 10}Prob > chi2 =  {res}  0.7029

{com}. test c6=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c6 - [unpetitionq22]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.18
{txt}{col 10}Prob > chi2 =  {res}  0.6752

{com}. test c6=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c6 - [unpetitionq22]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.96
{txt}{col 10}Prob > chi2 =  {res}  0.3279

{com}. test c7=c8

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c7 - [unpetitionq22]c8 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.04
{txt}{col 10}Prob > chi2 =  {res}  0.8365

{com}. test c7=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c7 - [unpetitionq22]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.13
{txt}{col 10}Prob > chi2 =  {res}  0.7209

{com}. test c7=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c7 - [unpetitionq22]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.99
{txt}{col 10}Prob > chi2 =  {res}  0.1582

{com}. test c7=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c7 - [unpetitionq22]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.37
{txt}{col 10}Prob > chi2 =  {res}  0.5444

{com}. test c7=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c7 - [unpetitionq22]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.00
{txt}{col 10}Prob > chi2 =  {res}  0.9545

{com}. test c8=c9

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c8 - [unpetitionq22]c9 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.02
{txt}{col 10}Prob > chi2 =  {res}  0.8835

{com}. test c8=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c8 - [unpetitionq22]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.41
{txt}{col 10}Prob > chi2 =  {res}  0.2345

{com}. test c8=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c8 - [unpetitionq22]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.15
{txt}{col 10}Prob > chi2 =  {res}  0.6939

{com}. test c8=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c8 - [unpetitionq22]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.02
{txt}{col 10}Prob > chi2 =  {res}  0.8792

{com}. test c9=c10

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c9 - [unpetitionq22]c10 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.11
{txt}{col 10}Prob > chi2 =  {res}  0.2915

{com}. test c9=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c9 - [unpetitionq22]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.06
{txt}{col 10}Prob > chi2 =  {res}  0.8024

{com}. test c9=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c9 - [unpetitionq22]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.09
{txt}{col 10}Prob > chi2 =  {res}  0.7618

{com}. test c10=c11

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c10 - [unpetitionq22]c11 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.64
{txt}{col 10}Prob > chi2 =  {res}  0.4223

{com}. test c10=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c10 - [unpetitionq22]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    1.88
{txt}{col 10}Prob > chi2 =  {res}  0.1708

{com}. test c11=c12

{p 0 7}{space 1}{text:( 1)}{space 1} {res}[unpetitionq22]c11 - [unpetitionq22]c12 = 0{p_end}

{txt}{col 12}chi2(  1) ={res}    0.31
{txt}{col 10}Prob > chi2 =  {res}  0.5787

{com}. 
. 
. 
. * * * Models Testing Causal Mechanisms (Tables 4-5): * * *

. ologit knowq1new c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2479.0257}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2384.2441}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2383.4989}  
Iteration 3:{space 3}log pseudolikelihood = {res:-2383.4982}  
Iteration 4:{space 3}log pseudolikelihood = {res:-2383.4982}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1801
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    175.68
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-2383.4982{txt}{col 51}Pseudo R2{col 67}= {res}    0.0385

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   knowq1new{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2} 1.031674{col 26}{space 2}  .214842{col 37}{space 1}    4.80{col 46}{space 3}0.000{col 54}{space 4} .6105911{col 67}{space 3} 1.452756
{txt}{space 10}c3 {c |}{col 14}{res}{space 2}  .094071{col 26}{space 2} .2382277{col 37}{space 1}    0.39{col 46}{space 3}0.693{col 54}{space 4}-.3728467{col 67}{space 3} .5609887
{txt}{space 10}c4 {c |}{col 14}{res}{space 2}-.1193825{col 26}{space 2} .2400971{col 37}{space 1}   -0.50{col 46}{space 3}0.619{col 54}{space 4}-.5899643{col 67}{space 3} .3511992
{txt}{space 10}c5 {c |}{col 14}{res}{space 2}-.1739317{col 26}{space 2} .2295934{col 37}{space 1}   -0.76{col 46}{space 3}0.449{col 54}{space 4}-.6239265{col 67}{space 3} .2760631
{txt}{space 10}c6 {c |}{col 14}{res}{space 2} 1.105925{col 26}{space 2} .2317812{col 37}{space 1}    4.77{col 46}{space 3}0.000{col 54}{space 4} .6516425{col 67}{space 3} 1.560208
{txt}{space 10}c7 {c |}{col 14}{res}{space 2} .6751859{col 26}{space 2} .2170293{col 37}{space 1}    3.11{col 46}{space 3}0.002{col 54}{space 4} .2498162{col 67}{space 3} 1.100556
{txt}{space 10}c8 {c |}{col 14}{res}{space 2} .7590864{col 26}{space 2} .2206657{col 37}{space 1}    3.44{col 46}{space 3}0.001{col 54}{space 4} .3265895{col 67}{space 3} 1.191583
{txt}{space 10}c9 {c |}{col 14}{res}{space 2} .3109305{col 26}{space 2} .2165266{col 37}{space 1}    1.44{col 46}{space 3}0.151{col 54}{space 4}-.1134538{col 67}{space 3} .7353148
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} .5592503{col 26}{space 2} .2265751{col 37}{space 1}    2.47{col 46}{space 3}0.014{col 54}{space 4} .1151712{col 67}{space 3} 1.003329
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} .6992569{col 26}{space 2} .2328306{col 37}{space 1}    3.00{col 46}{space 3}0.003{col 54}{space 4} .2429174{col 67}{space 3} 1.155596
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} 1.031659{col 26}{space 2} .2245811{col 37}{space 1}    4.59{col 46}{space 3}0.000{col 54}{space 4} .5914883{col 67}{space 3}  1.47183
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2}-.0127641{col 26}{space 2} .0044977{col 37}{space 1}   -2.84{col 46}{space 3}0.005{col 54}{space 4}-.0215795{col 67}{space 3}-.0039487
{txt}genderq14new {c |}{col 14}{res}{space 2} .0719277{col 26}{space 2} .0923813{col 37}{space 1}    0.78{col 46}{space 3}0.436{col 54}{space 4}-.1091364{col 67}{space 3} .2529917
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2}-.0543762{col 26}{space 2} .0336561{col 37}{space 1}   -1.62{col 46}{space 3}0.106{col 54}{space 4}-.1203409{col 67}{space 3} .0115885
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .2673664{col 26}{space 2} .0436459{col 37}{space 1}    6.13{col 46}{space 3}0.000{col 54}{space 4}  .181822{col 67}{space 3} .3529107
{txt}influenceq~w {c |}{col 14}{res}{space 2} .4113315{col 26}{space 2} .0659071{col 37}{space 1}    6.24{col 46}{space 3}0.000{col 54}{space 4} .2821559{col 67}{space 3} .5405071
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-1.025204{col 26}{space 2} .3193907{col 54}{space 4}-1.651198{col 67}{space 3}-.3992095
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2} .9102994{col 26}{space 2} .3089829{col 54}{space 4}  .304704{col 67}{space 3} 1.515895
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2} 1.899786{col 26}{space 2}  .311297{col 54}{space 4} 1.289655{col 67}{space 3} 2.509917
{col 1}{txt}       /cut4{col 14}{c |}{res}{space 2} 4.773902{col 26}{space 2} .3352381{col 54}{space 4} 4.116847{col 67}{space 3} 5.430957
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit knowconseqsq3new c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2378.9471}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2338.0084}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2337.8017}  
Iteration 3:{space 3}log pseudolikelihood = {res:-2337.8017}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1802
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}     78.05
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-2337.8017{txt}{col 51}Pseudo R2{col 67}= {res}    0.0173

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}knowconseq~w{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2} .3867542{col 26}{space 2} .2159431{col 37}{space 1}    1.79{col 46}{space 3}0.073{col 54}{space 4}-.0364865{col 67}{space 3}  .809995
{txt}{space 10}c3 {c |}{col 14}{res}{space 2}-.0837235{col 26}{space 2} .2453508{col 37}{space 1}   -0.34{col 46}{space 3}0.733{col 54}{space 4}-.5646023{col 67}{space 3} .3971553
{txt}{space 10}c4 {c |}{col 14}{res}{space 2} .0743484{col 26}{space 2} .2447587{col 37}{space 1}    0.30{col 46}{space 3}0.761{col 54}{space 4}-.4053699{col 67}{space 3} .5540666
{txt}{space 10}c5 {c |}{col 14}{res}{space 2}-.4079766{col 26}{space 2} .2318977{col 37}{space 1}   -1.76{col 46}{space 3}0.079{col 54}{space 4}-.8624877{col 67}{space 3} .0465344
{txt}{space 10}c6 {c |}{col 14}{res}{space 2} .4022541{col 26}{space 2}  .222299{col 37}{space 1}    1.81{col 46}{space 3}0.070{col 54}{space 4}-.0334439{col 67}{space 3} .8379521
{txt}{space 10}c7 {c |}{col 14}{res}{space 2} .2246792{col 26}{space 2} .2200154{col 37}{space 1}    1.02{col 46}{space 3}0.307{col 54}{space 4}-.2065431{col 67}{space 3} .6559016
{txt}{space 10}c8 {c |}{col 14}{res}{space 2} .2414673{col 26}{space 2} .2333336{col 37}{space 1}    1.03{col 46}{space 3}0.301{col 54}{space 4}-.2158582{col 67}{space 3} .6987928
{txt}{space 10}c9 {c |}{col 14}{res}{space 2}-.0605366{col 26}{space 2} .2305177{col 37}{space 1}   -0.26{col 46}{space 3}0.793{col 54}{space 4}-.5123431{col 67}{space 3} .3912699
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} .1213513{col 26}{space 2} .2255104{col 37}{space 1}    0.54{col 46}{space 3}0.590{col 54}{space 4} -.320641{col 67}{space 3} .5633436
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} .3539593{col 26}{space 2}  .239793{col 37}{space 1}    1.48{col 46}{space 3}0.140{col 54}{space 4}-.1160263{col 67}{space 3} .8239449
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} .3046722{col 26}{space 2} .2255222{col 37}{space 1}    1.35{col 46}{space 3}0.177{col 54}{space 4}-.1373432{col 67}{space 3} .7466876
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2}-.0199188{col 26}{space 2} .0046111{col 37}{space 1}   -4.32{col 46}{space 3}0.000{col 54}{space 4}-.0289563{col 67}{space 3}-.0108813
{txt}genderq14new {c |}{col 14}{res}{space 2}-.1144686{col 26}{space 2} .0953363{col 37}{space 1}   -1.20{col 46}{space 3}0.230{col 54}{space 4}-.3013243{col 67}{space 3} .0723871
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2} -.112319{col 26}{space 2} .0350782{col 37}{space 1}   -3.20{col 46}{space 3}0.001{col 54}{space 4}-.1810711{col 67}{space 3} -.043567
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .2009689{col 26}{space 2} .0427641{col 37}{space 1}    4.70{col 46}{space 3}0.000{col 54}{space 4} .1171529{col 67}{space 3}  .284785
{txt}influenceq~w {c |}{col 14}{res}{space 2}   .22137{col 26}{space 2} .0660321{col 37}{space 1}    3.35{col 46}{space 3}0.001{col 54}{space 4} .0919494{col 67}{space 3} .3507905
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-3.177193{col 26}{space 2} .3470867{col 54}{space 4} -3.85747{col 67}{space 3}-2.496915
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2} -1.15291{col 26}{space 2} .3176894{col 54}{space 4} -1.77557{col 67}{space 3}-.5302505
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2}-.2194907{col 26}{space 2} .3132538{col 54}{space 4}-.8334569{col 67}{space 3} .3944755
{col 1}{txt}       /cut4{col 14}{c |}{res}{space 2} 2.422881{col 26}{space 2} .3204645{col 54}{space 4} 1.794782{col 67}{space 3}  3.05098
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit knoweffectq5new c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2505.8748}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2409.1183}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2408.3616}  
Iteration 3:{space 3}log pseudolikelihood = {res: -2408.361}  
Iteration 4:{space 3}log pseudolikelihood = {res: -2408.361}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1801
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    170.68
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res} -2408.361{txt}{col 51}Pseudo R2{col 67}= {res}    0.0389

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}knoweffect~w{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2} 1.255815{col 26}{space 2} .2106881{col 37}{space 1}    5.96{col 46}{space 3}0.000{col 54}{space 4} .8428742{col 67}{space 3} 1.668757
{txt}{space 10}c3 {c |}{col 14}{res}{space 2} .1751862{col 26}{space 2}  .228781{col 37}{space 1}    0.77{col 46}{space 3}0.444{col 54}{space 4}-.2732163{col 67}{space 3} .6235887
{txt}{space 10}c4 {c |}{col 14}{res}{space 2} .0670803{col 26}{space 2} .2276533{col 37}{space 1}    0.29{col 46}{space 3}0.768{col 54}{space 4}-.3791119{col 67}{space 3} .5132725
{txt}{space 10}c5 {c |}{col 14}{res}{space 2} .0155715{col 26}{space 2} .2122214{col 37}{space 1}    0.07{col 46}{space 3}0.942{col 54}{space 4}-.4003748{col 67}{space 3} .4315179
{txt}{space 10}c6 {c |}{col 14}{res}{space 2} 1.308096{col 26}{space 2} .2199245{col 37}{space 1}    5.95{col 46}{space 3}0.000{col 54}{space 4} .8770518{col 67}{space 3}  1.73914
{txt}{space 10}c7 {c |}{col 14}{res}{space 2} .8949023{col 26}{space 2} .2091317{col 37}{space 1}    4.28{col 46}{space 3}0.000{col 54}{space 4} .4850117{col 67}{space 3} 1.304793
{txt}{space 10}c8 {c |}{col 14}{res}{space 2} 1.050986{col 26}{space 2} .2258325{col 37}{space 1}    4.65{col 46}{space 3}0.000{col 54}{space 4} .6083626{col 67}{space 3}  1.49361
{txt}{space 10}c9 {c |}{col 14}{res}{space 2} .6014572{col 26}{space 2} .2111005{col 37}{space 1}    2.85{col 46}{space 3}0.004{col 54}{space 4} .1877077{col 67}{space 3} 1.015207
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} .7842867{col 26}{space 2} .2079342{col 37}{space 1}    3.77{col 46}{space 3}0.000{col 54}{space 4} .3767432{col 67}{space 3}  1.19183
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} 1.017734{col 26}{space 2} .2309919{col 37}{space 1}    4.41{col 46}{space 3}0.000{col 54}{space 4} .5649985{col 67}{space 3}  1.47047
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} 1.124884{col 26}{space 2} .2219609{col 37}{space 1}    5.07{col 46}{space 3}0.000{col 54}{space 4} .6898489{col 67}{space 3}  1.55992
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2}-.0099256{col 26}{space 2} .0044967{col 37}{space 1}   -2.21{col 46}{space 3}0.027{col 54}{space 4} -.018739{col 67}{space 3}-.0011123
{txt}genderq14new {c |}{col 14}{res}{space 2} .2663618{col 26}{space 2} .0948052{col 37}{space 1}    2.81{col 46}{space 3}0.005{col 54}{space 4}  .080547{col 67}{space 3} .4521767
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2}-.0231232{col 26}{space 2} .0348828{col 37}{space 1}   -0.66{col 46}{space 3}0.507{col 54}{space 4}-.0914922{col 67}{space 3} .0452458
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .2449588{col 26}{space 2} .0425678{col 37}{space 1}    5.75{col 46}{space 3}0.000{col 54}{space 4} .1615275{col 67}{space 3} .3283902
{txt}influenceq~w {c |}{col 14}{res}{space 2} .3402048{col 26}{space 2} .0655074{col 37}{space 1}    5.19{col 46}{space 3}0.000{col 54}{space 4} .2118128{col 67}{space 3} .4685969
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-.8892627{col 26}{space 2}  .314012{col 54}{space 4}-1.504715{col 67}{space 3}-.2738106
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2} 1.227627{col 26}{space 2} .3010524{col 54}{space 4} .6375751{col 67}{space 3} 1.817679
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2} 2.225538{col 26}{space 2} .3055955{col 54}{space 4} 1.626582{col 67}{space 3} 2.824495
{col 1}{txt}       /cut4{col 14}{c |}{res}{space 2} 4.871914{col 26}{space 2}  .329271{col 54}{space 4} 4.226555{col 67}{space 3} 5.517273
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit conseqsq4new c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -2183.978}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2126.6706}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2126.3269}  
Iteration 3:{space 3}log pseudolikelihood = {res:-2126.3268}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1797
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    112.28
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-2126.3268{txt}{col 51}Pseudo R2{col 67}= {res}    0.0264

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}conseqsq4new{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2}-.1271071{col 26}{space 2} .1998974{col 37}{space 1}   -0.64{col 46}{space 3}0.525{col 54}{space 4}-.5188988{col 67}{space 3} .2646846
{txt}{space 10}c3 {c |}{col 14}{res}{space 2} .6479172{col 26}{space 2}  .205094{col 37}{space 1}    3.16{col 46}{space 3}0.002{col 54}{space 4} .2459405{col 67}{space 3} 1.049894
{txt}{space 10}c4 {c |}{col 14}{res}{space 2} .6027593{col 26}{space 2} .2138915{col 37}{space 1}    2.82{col 46}{space 3}0.005{col 54}{space 4} .1835396{col 67}{space 3} 1.021979
{txt}{space 10}c5 {c |}{col 14}{res}{space 2}-.3920486{col 26}{space 2} .2196154{col 37}{space 1}   -1.79{col 46}{space 3}0.074{col 54}{space 4} -.822487{col 67}{space 3} .0383897
{txt}{space 10}c6 {c |}{col 14}{res}{space 2} .7177351{col 26}{space 2} .1976903{col 37}{space 1}    3.63{col 46}{space 3}0.000{col 54}{space 4} .3302693{col 67}{space 3} 1.105201
{txt}{space 10}c7 {c |}{col 14}{res}{space 2} .6776239{col 26}{space 2}  .194772{col 37}{space 1}    3.48{col 46}{space 3}0.001{col 54}{space 4} .2958779{col 67}{space 3}  1.05937
{txt}{space 10}c8 {c |}{col 14}{res}{space 2}-.1272112{col 26}{space 2}  .215587{col 37}{space 1}   -0.59{col 46}{space 3}0.555{col 54}{space 4} -.549754{col 67}{space 3} .2953316
{txt}{space 10}c9 {c |}{col 14}{res}{space 2}  .516918{col 26}{space 2} .2152136{col 37}{space 1}    2.40{col 46}{space 3}0.016{col 54}{space 4} .0951071{col 67}{space 3}  .938729
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} .5152379{col 26}{space 2}   .22624{col 37}{space 1}    2.28{col 46}{space 3}0.023{col 54}{space 4} .0718157{col 67}{space 3} .9586602
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} .6173308{col 26}{space 2} .2116442{col 37}{space 1}    2.92{col 46}{space 3}0.004{col 54}{space 4} .2025159{col 67}{space 3} 1.032146
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} .3709784{col 26}{space 2} .1991496{col 37}{space 1}    1.86{col 46}{space 3}0.062{col 54}{space 4}-.0193477{col 67}{space 3} .7613045
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2}-.0205756{col 26}{space 2}  .004341{col 37}{space 1}   -4.74{col 46}{space 3}0.000{col 54}{space 4}-.0290837{col 67}{space 3}-.0120675
{txt}genderq14new {c |}{col 14}{res}{space 2} -.495737{col 26}{space 2} .0940581{col 37}{space 1}   -5.27{col 46}{space 3}0.000{col 54}{space 4}-.6800875{col 67}{space 3}-.3113864
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2}-.0467735{col 26}{space 2}   .03531{col 37}{space 1}   -1.32{col 46}{space 3}0.185{col 54}{space 4}-.1159797{col 67}{space 3} .0224328
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .1721755{col 26}{space 2} .0439695{col 37}{space 1}    3.92{col 46}{space 3}0.000{col 54}{space 4} .0859968{col 67}{space 3} .2583541
{txt}influenceq~w {c |}{col 14}{res}{space 2}-.0502831{col 26}{space 2} .0632397{col 37}{space 1}   -0.80{col 46}{space 3}0.427{col 54}{space 4}-.1742306{col 67}{space 3} .0736645
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-4.976366{col 26}{space 2} .3878144{col 54}{space 4}-5.736469{col 67}{space 3}-4.216264
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2}-3.171874{col 26}{space 2} .3126676{col 54}{space 4}-3.784692{col 67}{space 3}-2.559057
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2}-1.563368{col 26}{space 2} .2951085{col 54}{space 4} -2.14177{col 67}{space 3}-.9849657
{col 1}{txt}       /cut4{col 14}{c |}{res}{space 2} .4937544{col 26}{space 2} .2920033{col 54}{space 4}-.0785615{col 67}{space 3}  1.06607
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit ineffectq2new c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2722.9414}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2676.9916}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2676.8668}  
Iteration 3:{space 3}log pseudolikelihood = {res:-2676.8668}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1798
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}     93.11
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-2676.8668{txt}{col 51}Pseudo R2{col 67}= {res}    0.0169

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}ineffectq2~w{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2} .6323028{col 26}{space 2} .1812464{col 37}{space 1}    3.49{col 46}{space 3}0.000{col 54}{space 4} .2770664{col 67}{space 3} .9875391
{txt}{space 10}c3 {c |}{col 14}{res}{space 2} .4852068{col 26}{space 2} .1827601{col 37}{space 1}    2.65{col 46}{space 3}0.008{col 54}{space 4} .1270037{col 67}{space 3} .8434099
{txt}{space 10}c4 {c |}{col 14}{res}{space 2}  .385315{col 26}{space 2} .2200374{col 37}{space 1}    1.75{col 46}{space 3}0.080{col 54}{space 4}-.0459503{col 67}{space 3} .8165803
{txt}{space 10}c5 {c |}{col 14}{res}{space 2} .1492052{col 26}{space 2} .1548022{col 37}{space 1}    0.96{col 46}{space 3}0.335{col 54}{space 4}-.1542015{col 67}{space 3} .4526119
{txt}{space 10}c6 {c |}{col 14}{res}{space 2} .8941308{col 26}{space 2}  .190858{col 37}{space 1}    4.68{col 46}{space 3}0.000{col 54}{space 4}  .520056{col 67}{space 3} 1.268206
{txt}{space 10}c7 {c |}{col 14}{res}{space 2} 1.224019{col 26}{space 2} .2045526{col 37}{space 1}    5.98{col 46}{space 3}0.000{col 54}{space 4} .8231036{col 67}{space 3} 1.624935
{txt}{space 10}c8 {c |}{col 14}{res}{space 2} .5434604{col 26}{space 2} .1845217{col 37}{space 1}    2.95{col 46}{space 3}0.003{col 54}{space 4} .1818045{col 67}{space 3} .9051163
{txt}{space 10}c9 {c |}{col 14}{res}{space 2} .4446309{col 26}{space 2} .2012281{col 37}{space 1}    2.21{col 46}{space 3}0.027{col 54}{space 4} .0502312{col 67}{space 3} .8390307
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} 1.006197{col 26}{space 2} .2178079{col 37}{space 1}    4.62{col 46}{space 3}0.000{col 54}{space 4} .5793014{col 67}{space 3} 1.433093
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} .6937001{col 26}{space 2} .1821261{col 37}{space 1}    3.81{col 46}{space 3}0.000{col 54}{space 4} .3367396{col 67}{space 3} 1.050661
{txt}{space 9}c12 {c |}{col 14}{res}{space 2}  .848163{col 26}{space 2} .1860416{col 37}{space 1}    4.56{col 46}{space 3}0.000{col 54}{space 4} .4835282{col 67}{space 3} 1.212798
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2}-.0041248{col 26}{space 2} .0044511{col 37}{space 1}   -0.93{col 46}{space 3}0.354{col 54}{space 4}-.0128488{col 67}{space 3} .0045991
{txt}genderq14new {c |}{col 14}{res}{space 2}-.4364055{col 26}{space 2} .0950677{col 37}{space 1}   -4.59{col 46}{space 3}0.000{col 54}{space 4}-.6227347{col 67}{space 3}-.2500764
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2} .0113824{col 26}{space 2} .0335623{col 37}{space 1}    0.34{col 46}{space 3}0.735{col 54}{space 4}-.0543986{col 67}{space 3} .0771634
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .0916176{col 26}{space 2} .0401986{col 37}{space 1}    2.28{col 46}{space 3}0.023{col 54}{space 4} .0128297{col 67}{space 3} .1704055
{txt}influenceq~w {c |}{col 14}{res}{space 2} .0642205{col 26}{space 2}   .05976{col 37}{space 1}    1.07{col 46}{space 3}0.283{col 54}{space 4} -.052907{col 67}{space 3} .1813481
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-1.606851{col 26}{space 2} .2737393{col 54}{space 4} -2.14337{col 67}{space 3}-1.070332
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2}-.4703494{col 26}{space 2} .2679299{col 54}{space 4}-.9954824{col 67}{space 3} .0547836
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2} .2512536{col 26}{space 2} .2705165{col 54}{space 4} -.278949{col 67}{space 3} .7814562
{col 1}{txt}       /cut4{col 14}{c |}{res}{space 2} 1.515046{col 26}{space 2} .2754724{col 54}{space 4} .9751303{col 67}{space 3} 2.054962
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit emotionq7new c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2134.4528}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2049.1712}  
Iteration 2:{space 3}log pseudolikelihood = {res: -2048.361}  
Iteration 3:{space 3}log pseudolikelihood = {res:-2048.3602}  
Iteration 4:{space 3}log pseudolikelihood = {res:-2048.3602}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1800
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    163.41
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-2048.3602{txt}{col 51}Pseudo R2{col 67}= {res}    0.0403

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}emotionq7new{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2} .2701874{col 26}{space 2} .2119625{col 37}{space 1}    1.27{col 46}{space 3}0.202{col 54}{space 4}-.1452515{col 67}{space 3} .6856263
{txt}{space 10}c3 {c |}{col 14}{res}{space 2} 1.266886{col 26}{space 2}  .220084{col 37}{space 1}    5.76{col 46}{space 3}0.000{col 54}{space 4} .8355294{col 67}{space 3} 1.698243
{txt}{space 10}c4 {c |}{col 14}{res}{space 2} 1.232428{col 26}{space 2} .2238197{col 37}{space 1}    5.51{col 46}{space 3}0.000{col 54}{space 4} .7937496{col 67}{space 3} 1.671107
{txt}{space 10}c5 {c |}{col 14}{res}{space 2}-.2288863{col 26}{space 2} .2139856{col 37}{space 1}   -1.07{col 46}{space 3}0.285{col 54}{space 4}-.6482904{col 67}{space 3} .1905177
{txt}{space 10}c6 {c |}{col 14}{res}{space 2} .5882528{col 26}{space 2} .2157447{col 37}{space 1}    2.73{col 46}{space 3}0.006{col 54}{space 4} .1654009{col 67}{space 3} 1.011105
{txt}{space 10}c7 {c |}{col 14}{res}{space 2} .7839365{col 26}{space 2} .2158198{col 37}{space 1}    3.63{col 46}{space 3}0.000{col 54}{space 4} .3609376{col 67}{space 3} 1.206936
{txt}{space 10}c8 {c |}{col 14}{res}{space 2} .1785654{col 26}{space 2} .2168518{col 37}{space 1}    0.82{col 46}{space 3}0.410{col 54}{space 4}-.2464563{col 67}{space 3}  .603587
{txt}{space 10}c9 {c |}{col 14}{res}{space 2} .6724516{col 26}{space 2} .2215462{col 37}{space 1}    3.04{col 46}{space 3}0.002{col 54}{space 4}  .238229{col 67}{space 3} 1.106674
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} .6036179{col 26}{space 2} .2429576{col 37}{space 1}    2.48{col 46}{space 3}0.013{col 54}{space 4} .1274297{col 67}{space 3} 1.079806
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} .6689861{col 26}{space 2} .2138574{col 37}{space 1}    3.13{col 46}{space 3}0.002{col 54}{space 4} .2498333{col 67}{space 3} 1.088139
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} .1484657{col 26}{space 2} .2072424{col 37}{space 1}    0.72{col 46}{space 3}0.474{col 54}{space 4}-.2577218{col 67}{space 3} .5546533
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2} .0168835{col 26}{space 2} .0044904{col 37}{space 1}    3.76{col 46}{space 3}0.000{col 54}{space 4} .0080824{col 67}{space 3} .0256846
{txt}genderq14new {c |}{col 14}{res}{space 2}-.3373238{col 26}{space 2} .0960683{col 37}{space 1}   -3.51{col 46}{space 3}0.000{col 54}{space 4}-.5256142{col 67}{space 3}-.1490334
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2}-.0482963{col 26}{space 2} .0348485{col 37}{space 1}   -1.39{col 46}{space 3}0.166{col 54}{space 4}-.1165981{col 67}{space 3} .0200055
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .1378861{col 26}{space 2} .0435835{col 37}{space 1}    3.16{col 46}{space 3}0.002{col 54}{space 4}  .052464{col 67}{space 3} .2233082
{txt}influenceq~w {c |}{col 14}{res}{space 2} .2768767{col 26}{space 2} .0668931{col 37}{space 1}    4.14{col 46}{space 3}0.000{col 54}{space 4} .1457687{col 67}{space 3} .4079846
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2} -1.33122{col 26}{space 2} .3323352{col 54}{space 4}-1.982585{col 67}{space 3}-.6798552
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2} .6128626{col 26}{space 2} .3146737{col 54}{space 4}-.0038866{col 67}{space 3} 1.229612
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2} 2.817588{col 26}{space 2} .3225746{col 54}{space 4} 2.185354{col 67}{space 3} 3.449823
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit feelq8new c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2103.9373}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2029.0278}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2028.4273}  
Iteration 3:{space 3}log pseudolikelihood = {res:-2028.4268}  
Iteration 4:{space 3}log pseudolikelihood = {res:-2028.4268}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1800
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}    142.82
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-2028.4268{txt}{col 51}Pseudo R2{col 67}= {res}    0.0359

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}   feelq8new{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2}-.2396771{col 26}{space 2} .2043378{col 37}{space 1}   -1.17{col 46}{space 3}0.241{col 54}{space 4}-.6401718{col 67}{space 3} .1608176
{txt}{space 10}c3 {c |}{col 14}{res}{space 2}-1.067687{col 26}{space 2} .2132156{col 37}{space 1}   -5.01{col 46}{space 3}0.000{col 54}{space 4}-1.485582{col 67}{space 3} -.649792
{txt}{space 10}c4 {c |}{col 14}{res}{space 2}-1.230055{col 26}{space 2} .2187263{col 37}{space 1}   -5.62{col 46}{space 3}0.000{col 54}{space 4} -1.65875{col 67}{space 3}-.8013589
{txt}{space 10}c5 {c |}{col 14}{res}{space 2} .1717969{col 26}{space 2} .1964359{col 37}{space 1}    0.87{col 46}{space 3}0.382{col 54}{space 4}-.2132104{col 67}{space 3} .5568042
{txt}{space 10}c6 {c |}{col 14}{res}{space 2}-.7679351{col 26}{space 2} .2107689{col 37}{space 1}   -3.64{col 46}{space 3}0.000{col 54}{space 4}-1.181035{col 67}{space 3}-.3548356
{txt}{space 10}c7 {c |}{col 14}{res}{space 2}-.9612835{col 26}{space 2} .2261618{col 37}{space 1}   -4.25{col 46}{space 3}0.000{col 54}{space 4}-1.404552{col 67}{space 3}-.5180145
{txt}{space 10}c8 {c |}{col 14}{res}{space 2}-.2686775{col 26}{space 2} .2046581{col 37}{space 1}   -1.31{col 46}{space 3}0.189{col 54}{space 4}   -.6698{col 67}{space 3}  .132445
{txt}{space 10}c9 {c |}{col 14}{res}{space 2}-.8714534{col 26}{space 2} .2094618{col 37}{space 1}   -4.16{col 46}{space 3}0.000{col 54}{space 4}-1.281991{col 67}{space 3}-.4609158
{txt}{space 9}c10 {c |}{col 14}{res}{space 2}-1.094393{col 26}{space 2} .2180663{col 37}{space 1}   -5.02{col 46}{space 3}0.000{col 54}{space 4}-1.521795{col 67}{space 3}-.6669912
{txt}{space 9}c11 {c |}{col 14}{res}{space 2}-.5911786{col 26}{space 2} .2104131{col 37}{space 1}   -2.81{col 46}{space 3}0.005{col 54}{space 4}-1.003581{col 67}{space 3}-.1787764
{txt}{space 9}c12 {c |}{col 14}{res}{space 2}  -.67628{col 26}{space 2} .2077351{col 37}{space 1}   -3.26{col 46}{space 3}0.001{col 54}{space 4}-1.083433{col 67}{space 3}-.2691268
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2} .0009535{col 26}{space 2} .0043371{col 37}{space 1}    0.22{col 46}{space 3}0.826{col 54}{space 4} -.007547{col 67}{space 3} .0094541
{txt}genderq14new {c |}{col 14}{res}{space 2} .5349042{col 26}{space 2} .0944278{col 37}{space 1}    5.66{col 46}{space 3}0.000{col 54}{space 4} .3498291{col 67}{space 3} .7199793
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2}  .019611{col 26}{space 2} .0366816{col 37}{space 1}    0.53{col 46}{space 3}0.593{col 54}{space 4}-.0522835{col 67}{space 3} .0915055
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2}-.2103669{col 26}{space 2} .0447636{col 37}{space 1}   -4.70{col 46}{space 3}0.000{col 54}{space 4} -.298102{col 67}{space 3}-.1226317
{txt}influenceq~w {c |}{col 14}{res}{space 2} .1428011{col 26}{space 2} .0676957{col 37}{space 1}    2.11{col 46}{space 3}0.035{col 54}{space 4}   .01012{col 67}{space 3} .2754823
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-1.392595{col 26}{space 2} .3028878{col 54}{space 4}-1.986245{col 67}{space 3}-.7989462
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2} .7867549{col 26}{space 2} .3023227{col 54}{space 4} .1942133{col 67}{space 3} 1.379297
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2} 2.651265{col 26}{space 2} .3173666{col 54}{space 4} 2.029238{col 67}{space 3} 3.273292
{col 1}{txt}       /cut4{col 14}{c |}{res}{space 2} 4.064762{col 26}{space 2} .3788608{col 54}{space 4} 3.322209{col 67}{space 3} 4.807316
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit feelconseqsq9new c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2311.8582}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2267.4757}  
Iteration 2:{space 3}log pseudolikelihood = {res:-2267.1769}  
Iteration 3:{space 3}log pseudolikelihood = {res:-2267.1768}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1796
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}     88.23
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res}-2267.1768{txt}{col 51}Pseudo R2{col 67}= {res}    0.0193

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}feelconseq~w{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2} .2342651{col 26}{space 2} .2048867{col 37}{space 1}    1.14{col 46}{space 3}0.253{col 54}{space 4}-.1673054{col 67}{space 3} .6358356
{txt}{space 10}c3 {c |}{col 14}{res}{space 2}  .804134{col 26}{space 2} .2154085{col 37}{space 1}    3.73{col 46}{space 3}0.000{col 54}{space 4} .3819412{col 67}{space 3} 1.226327
{txt}{space 10}c4 {c |}{col 14}{res}{space 2} .6148784{col 26}{space 2} .2233357{col 37}{space 1}    2.75{col 46}{space 3}0.006{col 54}{space 4} .1771484{col 67}{space 3} 1.052608
{txt}{space 10}c5 {c |}{col 14}{res}{space 2}-.3297695{col 26}{space 2} .2013782{col 37}{space 1}   -1.64{col 46}{space 3}0.102{col 54}{space 4}-.7244635{col 67}{space 3} .0649245
{txt}{space 10}c6 {c |}{col 14}{res}{space 2} .7667785{col 26}{space 2} .2079657{col 37}{space 1}    3.69{col 46}{space 3}0.000{col 54}{space 4} .3591732{col 67}{space 3} 1.174384
{txt}{space 10}c7 {c |}{col 14}{res}{space 2} .7370494{col 26}{space 2}   .20849{col 37}{space 1}    3.54{col 46}{space 3}0.000{col 54}{space 4} .3284166{col 67}{space 3} 1.145682
{txt}{space 10}c8 {c |}{col 14}{res}{space 2} .2164009{col 26}{space 2} .2102695{col 37}{space 1}    1.03{col 46}{space 3}0.303{col 54}{space 4}-.1957198{col 67}{space 3} .6285217
{txt}{space 10}c9 {c |}{col 14}{res}{space 2} .3543093{col 26}{space 2} .2227019{col 37}{space 1}    1.59{col 46}{space 3}0.112{col 54}{space 4}-.0821784{col 67}{space 3} .7907971
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} .6051153{col 26}{space 2} .2281567{col 37}{space 1}    2.65{col 46}{space 3}0.008{col 54}{space 4} .1579363{col 67}{space 3} 1.052294
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} .4276474{col 26}{space 2} .2151284{col 37}{space 1}    1.99{col 46}{space 3}0.047{col 54}{space 4} .0060035{col 67}{space 3} .8492913
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} .6441688{col 26}{space 2}   .21341{col 37}{space 1}    3.02{col 46}{space 3}0.003{col 54}{space 4} .2258928{col 67}{space 3} 1.062445
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2} -.011159{col 26}{space 2} .0044838{col 37}{space 1}   -2.49{col 46}{space 3}0.013{col 54}{space 4}-.0199471{col 67}{space 3}-.0023708
{txt}genderq14new {c |}{col 14}{res}{space 2}-.4195598{col 26}{space 2} .0956747{col 37}{space 1}   -4.39{col 46}{space 3}0.000{col 54}{space 4}-.6070787{col 67}{space 3}-.2320408
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2}-.0098103{col 26}{space 2} .0350832{col 37}{space 1}   -0.28{col 46}{space 3}0.780{col 54}{space 4}-.0785721{col 67}{space 3} .0589515
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .1770968{col 26}{space 2} .0424889{col 37}{space 1}    4.17{col 46}{space 3}0.000{col 54}{space 4} .0938202{col 67}{space 3} .2603735
{txt}influenceq~w {c |}{col 14}{res}{space 2} .0433732{col 26}{space 2} .0640592{col 37}{space 1}    0.68{col 46}{space 3}0.498{col 54}{space 4}-.0821805{col 67}{space 3}  .168927
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-3.365691{col 26}{space 2} .3540637{col 54}{space 4}-4.059643{col 67}{space 3}-2.671739
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2}-1.542842{col 26}{space 2} .3097012{col 54}{space 4}-2.149845{col 67}{space 3} -.935839
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2} -.407581{col 26}{space 2} .3068452{col 54}{space 4}-1.008986{col 67}{space 3} .1938245
{col 1}{txt}       /cut4{col 14}{c |}{res}{space 2} 1.895724{col 26}{space 2} .3116073{col 54}{space 4} 1.284985{col 67}{space 3} 2.506463
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit feeleffectq10new c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news influenceq18new if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res:-2476.9037}  
Iteration 1:{space 3}log pseudolikelihood = {res:-2443.7266}  
Iteration 2:{space 3}log pseudolikelihood = {res: -2443.601}  
Iteration 3:{space 3}log pseudolikelihood = {res: -2443.601}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1796
{txt}{col 51}Wald chi2({res}16{txt}){col 67}= {res}     66.26
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0000
{txt}Log pseudolikelihood = {res} -2443.601{txt}{col 51}Pseudo R2{col 67}= {res}    0.0134

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}feeleffect~w{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2} .5599902{col 26}{space 2} .2072066{col 37}{space 1}    2.70{col 46}{space 3}0.007{col 54}{space 4} .1538727{col 67}{space 3} .9661078
{txt}{space 10}c3 {c |}{col 14}{res}{space 2} .4945892{col 26}{space 2} .2048299{col 37}{space 1}    2.41{col 46}{space 3}0.016{col 54}{space 4} .0931299{col 67}{space 3} .8960485
{txt}{space 10}c4 {c |}{col 14}{res}{space 2} .3381744{col 26}{space 2} .2301502{col 37}{space 1}    1.47{col 46}{space 3}0.142{col 54}{space 4}-.1129117{col 67}{space 3} .7892606
{txt}{space 10}c5 {c |}{col 14}{res}{space 2}  .062013{col 26}{space 2}  .185044{col 37}{space 1}    0.34{col 46}{space 3}0.738{col 54}{space 4}-.3006665{col 67}{space 3} .4246925
{txt}{space 10}c6 {c |}{col 14}{res}{space 2} .8023042{col 26}{space 2} .1984186{col 37}{space 1}    4.04{col 46}{space 3}0.000{col 54}{space 4} .4134109{col 67}{space 3} 1.191197
{txt}{space 10}c7 {c |}{col 14}{res}{space 2} 1.004086{col 26}{space 2}  .198384{col 37}{space 1}    5.06{col 46}{space 3}0.000{col 54}{space 4} .6152601{col 67}{space 3} 1.392911
{txt}{space 10}c8 {c |}{col 14}{res}{space 2} .7315887{col 26}{space 2} .1948384{col 37}{space 1}    3.75{col 46}{space 3}0.000{col 54}{space 4} .3497125{col 67}{space 3} 1.113465
{txt}{space 10}c9 {c |}{col 14}{res}{space 2}  .615774{col 26}{space 2} .1883874{col 37}{space 1}    3.27{col 46}{space 3}0.001{col 54}{space 4} .2465415{col 67}{space 3} .9850066
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} .7553103{col 26}{space 2} .2235347{col 37}{space 1}    3.38{col 46}{space 3}0.001{col 54}{space 4} .3171902{col 67}{space 3}  1.19343
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} .7557666{col 26}{space 2} .2045078{col 37}{space 1}    3.70{col 46}{space 3}0.000{col 54}{space 4} .3549387{col 67}{space 3} 1.156595
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} .9548613{col 26}{space 2} .1956871{col 37}{space 1}    4.88{col 46}{space 3}0.000{col 54}{space 4} .5713218{col 67}{space 3} 1.338401
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2}-.0016537{col 26}{space 2} .0045319{col 37}{space 1}   -0.36{col 46}{space 3}0.715{col 54}{space 4} -.010536{col 67}{space 3} .0072287
{txt}genderq14new {c |}{col 14}{res}{space 2}-.2120533{col 26}{space 2}  .092945{col 37}{space 1}   -2.28{col 46}{space 3}0.023{col 54}{space 4}-.3942222{col 67}{space 3}-.0298844
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2} .0081107{col 26}{space 2} .0338742{col 37}{space 1}    0.24{col 46}{space 3}0.811{col 54}{space 4}-.0582815{col 67}{space 3}  .074503
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .1371697{col 26}{space 2} .0428721{col 37}{space 1}    3.20{col 46}{space 3}0.001{col 54}{space 4}  .053142{col 67}{space 3} .2211974
{txt}influenceq~w {c |}{col 14}{res}{space 2} .0525914{col 26}{space 2} .0627878{col 37}{space 1}    0.84{col 46}{space 3}0.402{col 54}{space 4}-.0704705{col 67}{space 3} .1756532
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-2.231311{col 26}{space 2}  .297631{col 54}{space 4}-2.814657{col 67}{space 3}-1.647965
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2}-.6186851{col 26}{space 2}  .283385{col 54}{space 4} -1.17411{col 67}{space 3}-.0632607
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2}  .544733{col 26}{space 2} .2853208{col 54}{space 4}-.0144856{col 67}{space 3} 1.103952
{col 1}{txt}       /cut4{col 14}{c |}{res}{space 2}  2.65602{col 26}{space 2} .2951031{col 54}{space 4} 2.077628{col 67}{space 3} 3.234411
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. ologit influenceq18new c2 c3 c4 c5 c6 c7 c8 c9 c10 c11 c12 age genderq14new educ news  if captchadichotomous ==1, robust

{res}{txt}Iteration 0:{space 3}log pseudolikelihood = {res: -1979.818}  
Iteration 1:{space 3}log pseudolikelihood = {res:-1965.1719}  
Iteration 2:{space 3}log pseudolikelihood = {res: -1965.137}  
Iteration 3:{space 3}log pseudolikelihood = {res: -1965.137}  
{res}
{txt}Ordered logistic regression{col 51}Number of obs{col 67}= {res}      1803
{txt}{col 51}Wald chi2({res}15{txt}){col 67}= {res}     29.75
{txt}{col 51}Prob > chi2{col 67}= {res}    0.0129
{txt}Log pseudolikelihood = {res} -1965.137{txt}{col 51}Pseudo R2{col 67}= {res}    0.0074

{txt}{hline 13}{c TT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 14}{c |}{col 26}    Robust
{col 1}influenceq~w{col 14}{c |}      Coef.{col 26}   Std. Err.{col 38}      z{col 46}   P>|z|{col 54}     [95% Con{col 67}f. Interval]
{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{space 10}c2 {c |}{col 14}{res}{space 2}-.0356614{col 26}{space 2} .2435852{col 37}{space 1}   -0.15{col 46}{space 3}0.884{col 54}{space 4}-.5130796{col 67}{space 3} .4417568
{txt}{space 10}c3 {c |}{col 14}{res}{space 2} .0538256{col 26}{space 2} .2333989{col 37}{space 1}    0.23{col 46}{space 3}0.818{col 54}{space 4}-.4036279{col 67}{space 3} .5112791
{txt}{space 10}c4 {c |}{col 14}{res}{space 2} -.055988{col 26}{space 2} .2478953{col 37}{space 1}   -0.23{col 46}{space 3}0.821{col 54}{space 4}-.5418537{col 67}{space 3} .4298778
{txt}{space 10}c5 {c |}{col 14}{res}{space 2} .1177152{col 26}{space 2} .2305256{col 37}{space 1}    0.51{col 46}{space 3}0.610{col 54}{space 4}-.3341066{col 67}{space 3}  .569537
{txt}{space 10}c6 {c |}{col 14}{res}{space 2}-.0403392{col 26}{space 2} .2338103{col 37}{space 1}   -0.17{col 46}{space 3}0.863{col 54}{space 4}-.4985988{col 67}{space 3} .4179205
{txt}{space 10}c7 {c |}{col 14}{res}{space 2}   .02511{col 26}{space 2} .2307979{col 37}{space 1}    0.11{col 46}{space 3}0.913{col 54}{space 4}-.4272456{col 67}{space 3} .4774655
{txt}{space 10}c8 {c |}{col 14}{res}{space 2}-.0511203{col 26}{space 2} .2440356{col 37}{space 1}   -0.21{col 46}{space 3}0.834{col 54}{space 4}-.5294213{col 67}{space 3} .4271807
{txt}{space 10}c9 {c |}{col 14}{res}{space 2} .2091934{col 26}{space 2} .2363014{col 37}{space 1}    0.89{col 46}{space 3}0.376{col 54}{space 4}-.2539488{col 67}{space 3} .6723355
{txt}{space 9}c10 {c |}{col 14}{res}{space 2} .1098316{col 26}{space 2} .2442384{col 37}{space 1}    0.45{col 46}{space 3}0.653{col 54}{space 4}-.3688668{col 67}{space 3} .5885301
{txt}{space 9}c11 {c |}{col 14}{res}{space 2} .1165979{col 26}{space 2} .2487033{col 37}{space 1}    0.47{col 46}{space 3}0.639{col 54}{space 4}-.3708516{col 67}{space 3} .6040475
{txt}{space 9}c12 {c |}{col 14}{res}{space 2} .2913817{col 26}{space 2} .2307903{col 37}{space 1}    1.26{col 46}{space 3}0.207{col 54}{space 4}-.1609589{col 67}{space 3} .7437223
{txt}{space 6}ageq13 {c |}{col 14}{res}{space 2} -.013028{col 26}{space 2}  .004552{col 37}{space 1}   -2.86{col 46}{space 3}0.004{col 54}{space 4}-.0219498{col 67}{space 3}-.0041062
{txt}genderq14new {c |}{col 14}{res}{space 2}-.2060933{col 26}{space 2} .0945354{col 37}{space 1}   -2.18{col 46}{space 3}0.029{col 54}{space 4}-.3913793{col 67}{space 3}-.0208074
{txt}{space 5}educq15 {c |}{col 14}{res}{space 2}   .04619{col 26}{space 2} .0363932{col 37}{space 1}    1.27{col 46}{space 3}0.204{col 54}{space 4}-.0251393{col 67}{space 3} .1175193
{txt}{space 5}newsq16 {c |}{col 14}{res}{space 2} .1654573{col 26}{space 2} .0425324{col 37}{space 1}    3.89{col 46}{space 3}0.000{col 54}{space 4} .0820953{col 67}{space 3} .2488193
{txt}{hline 13}{c +}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}
{col 1}       /cut1{col 14}{c |}{res}{space 2}-1.112802{col 26}{space 2} .2945362{col 54}{space 4}-1.690082{col 67}{space 3}-.5355215
{col 1}{txt}       /cut2{col 14}{c |}{res}{space 2} 1.336338{col 26}{space 2} .2955167{col 54}{space 4} .7571354{col 67}{space 3}  1.91554
{col 1}{txt}       /cut3{col 14}{c |}{res}{space 2} 3.877392{col 26}{space 2} .3209873{col 54}{space 4} 3.248268{col 67}{space 3} 4.506516
{txt}{hline 13}{c BT}{hline 11}{hline 11}{hline 9}{hline 8}{hline 13}{hline 12}

{com}. 
. 
. 
. log close
      {txt}name:  {res}<unnamed>
       {txt}log:  {res}/Users/mkrain/Desktop/R&P-log.smcl
  {txt}log type:  {res}smcl
 {txt}closed on:  {res} 9 Sep 2016, 15:01:51
{txt}{.-}
{smcl}
{txt}{sf}{ul off}